The same is true for most US investors, who largely invest in domestically traded securities despite unbridled access to foreign markets. Direct ownership of non-USD-denominated securities is more of a rarity with the abundance of American Depositary Receipts (ADRs) available and a plethora of attractive opportunities at home. For some countries, investing domestically is more of a necessity; a byproduct of the friction in buying foreign stocks. India, for example, has liberalised access to foreign equities for individual investors in recent years, but there remains a hard cap on the value any one person can invest in a given year. In Vietnam, access to overseas brokerages is tightly controlled and subject to approval processes. However, situations like these tend to be the outliers. The United States, the UK, European Union members, Singapore, Hong Kong, Australia, Japan, Canada… all boast easy and cheap access to the corners of the world’s most important and liquid equity markets.

On the whole, FX can feel like optional exposure. Yet, avoidance of foreign exchange is possible in principle, but not in reality. Domestic equity can, at times, just be foreign revenue with a local ticker. For most large public companies, the customer base is global. They have divisions on multiple continents, earning sales in various currencies, all translated back to a single reporting currency.

Take the United Kingdom as one example. The London Stock Exchange Group suggests that in 2025, the FTSE 1001 (the index tracking the biggest UK stocks) “derives nearly 30% of its revenue from the United States, far outstripping contributions from other regions such as Japan and China”, highlighting the “critical role of the US economy in driving earnings for UK-listed companies”. You never truly escape FX risk.

If a tree falls in the forest, does it make a sound? Of course it does. While FX can be out of sight, out of mind, it’s still there. The ramifications still trickle their way into the market pricing machine’s outlook on share prices. I am certain that even the staunchest domestic investors will have read through earnings calls and filings and recall disclosures of figures presented in constant currency, commentary on FX headwinds, various footnotes on hedging gains and losses, and so on. Yet because this seldom amounts to more than a few percentage points of difference in reported figures and does not bear a direct cost to your P/L, it’s commonly glanced over and forgotten about.

It’s one of those things that only alarms you when there is cause for alarm. I’ll admit that it’s something I seldom think about too deeply. This is despite having only ~30% of my invested assets allocated to domestic equities. The remainder is invested across equities listed in the United States (USD) and Europe (EUR), relatively stable currency pairs during my lifetime as an investor (which isn’t a long timeline).

Recently, I have been studying a few businesses in Japan. Two examples are Fast Retailing and Kikkoman Corporation.

Fast Retailing (9983), owners of the splendid Uniqlo brand, which I think highly of. Their combination of high-quality materials at an affordable price point is unrivalled. An offering particularly relevant in a world suffering from the ramifications of high inflation. Their stores are immensely popular wherever I happen to find them. In the small island of Singapore, there are 29 stores of all shapes and sizes. During a recent trip in December, I must have visited 6 of them, and they were constantly packed with customers. I had a similar experience when travelling in Thailand in early 2025, which is home to 72 stores. Even in India, where I happen to spend a lot of time, Uniqlo is growing a presence here. In Scotland, they opened a large store a few years back in the capital city, in a second-rate location on the former shopping hub known as Princes Street. Even today, it welcomes droves of customers like its opening weekend.

Uniqlo is a household name across Japan, China, and the rest of Southeast Asia. In what sounds like a tantalising opportunity, the brand is relatively unknown in the West, with just over 100 stores in North America and 91 in Europe. In the last 12 months, Uniqlo’s store count has grown by 18% and 11% in North America and Europe, respectively. The company’s revenue and profits have been growing like a weed, but so too has the valuation.

I stuck it in the “unsure” pile with the intention of coming back to it in the future, and moved on. I liked the business, was excited about the reinvestment runway, but couldn’t get comfortable with the valuation.

Kikkoman Corporation (2801) is the manufacturer of the world’s most well-known soy sauce, Kikkoman, as well as a host of other consumer products like seasonings and milk products. A different animal from Fast Retailing. In comparison, Kikkoman is more of a stable, steady growth, income-bearing, stalwart type of holding. I don’t subscribe to labels related to investment style. I optimise for businesses I can understand and that I think will surpass my threshold for attractive returns. So long as I think they can overcome that hurdle, I don’t personally care if the CAGR ends up being 14% or 45%. Obviously, the latter is better, but I often see DIY investors fall victim to seeking only outsized returns and end up being long a single factor.

I saw potential in the business, and the valuation was more palatable. But I couldn’t escape the feeling that I was making a macro call as well as a fundamental decision. My expectation of the potential future returns of Kikkoman was closer to the lower end of my threshold than Fast Retailing (at a more attractive valuation). It was at this point that I started to think about the impact of FX.

With a high-flying growth style stock like Fast Retailing, a valid entry point could prove to be forgiving when total returns are considered. However, if something is expected to compound at, say, anywhere between 8% and 12%, then a few hundred basis points of FX impact either way can have a more visceral impact. Suppose that domestic investors in Kikkoman over the past decade would have earned a modest 7.7% CAGR with dividends. Not catastrophic by any means, but not fantastic. An investor from the United Kingdom, however, would have earned a 5.2% CAGR after the FX drag had been factored in.

Consider that the UK-listed S&P 500 index put up a 16% CAGR over the same period… Ultimately, Kikkoman was not for me. Yet I was interested in the self-reflection that I found myself thinking about FX considerably more than I usually do. I was not solely making an investment decision on fundamental grounds. I would also be making a macro call that the Yen would (preferably) strengthen post acquisition.

The Yen has weakened relative to the GBP in recent years. In fact, it’s the weakest it has been since 2008. The ideal case would be that the Yen strengthened until the time I come to sell, meaning I receive more GBP per unit of JPY sold. In my naive monkey brain, this seemed like a more likely outcome and would be a welcome tailwind should I own the stock for a period of five to ten years.

Line went up for long time, so now should go down for long time.

I’d hardly call myself a proficient fundamental investor, let alone a foreign exchange oracle. I would also have to contend with the state of the Japanese economy and its influence on exchange rates. I find the prospect of conviction in the face of volatile FX rates is harder to stomach than fundamental volatility. I am more confident in riding a storm when it comes to my understanding of whether the impacts on the business are temporary or structural. I am significantly less confident (or perhaps less deluded in my ability) when it comes to understanding if FX rates are going to be a short-term headwind or a decade-long handicap.

I noticed myself agonising over a factor I seldom considered at great length when purchasing US or European stocks. Yet, even for these established currency pairs, there have been periods of significant tide changes. Only, I am too young and too naive to appreciate them.

As a teenager, I recall hearing the adults in the room recall when you could get two US Dollars for a Pound. In my lifetime, the duration that I have been cognisant of units of exchange, at least, the going rate has oscillated between $1.20 to $1.45. History shows that the relationship between the US Dollar and the Great British Pound hasn’t always been so boring. There have been various periods across the last five decades, when one side of the pair has strengthened against the other by orders of magnitude ranging between 30% and 60%.

The United States is arguably the most attractive financial market in the world. It just so happens I was born in a country and at a time which has been characterised by a relatively stable foreign exchange with the United States. This, I believe, has created a sense of complacency in myself, and I suspect others, with regard to currency impacts. Perhaps it’s a sign of maturity that after a decade of investing, I begin to consider this risk that feels out of sight but could one day be front of mind. Perhaps it’s because this month I finished reading ‘The Asian Financial Crisis’ by Russell Napier, which discusses the intensity of currency flows during the 1997 crisis. Perhaps it’s a byproduct of compounding.

When I was younger, and my portfolio was smaller, I noticed the FX impacts on my P/L statement. But they were so small I didn’t think much about them. These days, the aggregate FX impact of my US and European holdings is something I pay a lot more attention to because the numbers are no longer so insignificant.

To provide an example, I have owned Alphabet since July 2022. That initial lot is now up 208% from its purchase price. However, if I were to sell it today, it would amount to a return of 173% after accounting for the FX drag. That’s a 35% reduction in performance. Comparatively, I have owned Apple since September 2018. The raw total return is 343%, with just a 10% reduction in return thanks to FX. While a few holdings are boasting FX gains, it nets out to an aggregate loss on the FX side of things for me. As the portfolio has grown, so too has the implicit cost of conducting affairs in foreign stocks. Not that I actively do anything about it, mind you.

The last year or two has been marked by a weakening US Dollar. Amongst some of the world’s most liquid currencies, the last year has been a handicap for foreign investors invested in US stocks. The US Dollar Index (DXY), which measures the performance of the USD relative to the world’s largest currencies, has declined2 by almost 10% in the last 12 months.

What does this mean for foreign investors? Let’s use an illustration from my own portfolio. Take the UK equivalent of the S&P 500 ETF, VUSA, as one example. While the US counterpart (SPY) has put up 18.3% total returns over the last 12 months, UK investors in VUSA have only seen 7.9% returns thanks to a stuttering Dollar. Thankfully for me, I also invest in the domestic market. The UK’s FTSE 100 ETF, VUKE, has returned an impressive 26.5% over the same period. Just don’t pull back the chart history any further…

The irony in my reflections is not lost on me. As it were, I have been making macro bets all along. Recency bias, stability bias, whatever you wish to call it, has created an illusion of safety for me. As Hyman Minsky famously said, “Stability is destabilising". The longer nothing bad happens, the more comfortable people become with risk, and the more risk people take.

Only when venturing into unfamiliar terrain (Japan, in this case) did, for me anyway, the same risk present itself more noticeably. As though I am now in earshot of the tree that falls in the forest.

To disappoint anyone reading, there is no strong meaning or takeaway behind this note. Perhaps you can infer your own. I write primarily to transfer thoughts onto paper in the hope that I can reflect on them with a clear mind. It is by airing my ignorances and naivety that I compel myself to do something about them and learn.

Thanks for reading,

Conor

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DXY 1Y Return

This day coincided with the third quarter earnings announcement from Chipotle Mexican Grill. The past few years have been tough for this once loved purveyor of proteins and vegetables. A few solid years of unabating global inflation had caused input costs to soar which, in turn, means menu inflation followed. It was around this period that Chipotle faced increasing backlash online about their portion sizes— both in terms of their inconsistency as well as the fact customers felt they were being shortchanged. Was this tactful internal policy to save margins or an unfortunately-timed gradual decline in the enforcement of standards? Who’s to say.

The fact of the matter is that this earned Chipotle a lot of bad press. So much so, that press releases and advertising campaigns were spun up to console angry customers and assure them more attention would be given to serving beefy portion sizes once more. A recurring theme throughout earnings calls of 2024 and 2025 was the company’s progress on setting the portion problem straight.

Below is a snippet from the first time the social media backlash was brought up during the company’s Q2 2024 results in July 2024.

“I want to take a minute to address the portion concerns that have been brought up in social media. First, there was never a directive to provide less to our customers. Generous portion is a core brand equity of Chipotle. It always has been, and it always will be. With that said, getting the feedback caused us to relook at our execution across our entire system with the intention to always serve our guests delicious, fresh, custom burritos and bowls with generous portions. To be more consistent across all 3,500 restaurants, we have focused in on those with outlier portion scores based on consumer surveys, and we are reemphasizing training and coaching around ensuring we are consistently making bowls and burritos correctly”.

- Brian Niccol, former CEO of Chipotle

Brian Niccol would leave shortly after, in August 2024, to join Starbucks. By November, Scott Boatwright, Chief Operating Office since 2017, was appointed.

The Coming of Slop

I don’t know exactly when the phrase entered the lexicon of the english-speaking world, but at some point Chipotle, and a handful of other quick-serve bowl-centric restaurants, began to adorn the title of “Slop”. Slop merchants. Bowls of slop. The era of slop. Slop fatigue. One of my favourite headlines1 read, ‘The slop bowl recession just sent Chipotle’s stock cratering’.

The date of this article was October 31st, 2025. The day after Chipotle reported their third quarter earnings for the year and the stock fell 18.2%. Only three times in history has the stock fell harder in a single day. Two occasions during the great financial crisis of 2008 when the company’s share price would fall ~20% within 2 months of each other. Once, in 2012, where Chipotle fell 22% after the E.coli scandal hit the headlines.

What was so calamitous in this earnings call that caused such a sudden recoil from investors? Following successive negative comparable sales, Chipotle managed to squeeze out a 0.3% improvement on comparable sales in that quarter. Restaurant margins decline 100bps YoY falling to a, still high by industry standards, 24.5%. Talks of macroeconomic pressures, results failing to live up to analyst expectations, yada yada yada. The objective truth of the matter is that Chipotle was still choking down the inflation from the post-pandemic era and it’s influence on the, now more sensitive, consumer.

With the mythical powers of hindsight, its clear that Chipotle sprayed the inflationary bazooka for a little too long. Instead of offsetting inflation, they were confident the consumer could absorb more price. Observing the 3 years before and after the pandemic (2020) are telling. In 2017, 2018, and 2019, Chipotle pushed through annual menu price increases of 1.2%, 2.4%, and 0.2%, respectively. In 2021, 2022, and 2023, the annual price hikes were 8.5%, 12.0% , and 5.2%. After pressure on transactions growth started to appear, Chipotle lowered the price inflation to 2.9% in 2024. Despite pushing price so hard, Chipotle’s consumers were unwavering. Comparable sales kept printing good numbers. Transactions, albeit with a wobble in 2022, continued to look strong too, with comps of 10.3%, 0.9%, 5.0%, and 5.3% in 2021, 2022, 2023, and 2024, respectively.

One could be forgiven for thinking that Chipotle knew something we didn’t. How could this business continue to raise prices even as inflation in the United States, Chipotle’s largest market, started to come back down to earth in early 2023? What made them so confident?

In early 2024, while discussing the company’s Q4 2023 results, former CFO John Hartung suggested that Chipotle could see restaurant-level margins as high as the “30% range” as the company approach $4 million average unit volumes.

“As we get up to $4 million, I would expect we’d be in the high 20%, maybe even in the 30% range. Again, you’re talking about predicting something over a very long period of time. But our margins will definitely get stronger over time, which means our returns will get stronger as well as we move from $3 million to $4 million”.

-John Hartung, former CFO of Chipotle

At the time, Chipotle had just reported 26.2%2 margins while simultaneously surpassing $3 million in AUV for the first time. In the following year, Hartung’s message would seem like gospel as margins increased 50bps and the AUV saw an incremental $190k improvement to $3.2 million.

All seemed well. There was some social media backlash against small portions. There was a change in CEO. The rise of the term “slop bowl” was becoming more prominent. But until around Q1 of 2025, Chipotle had showed few signs of fundamental deterioration. The stock marched on. By the end of 2024, Chipotle shares traded for ~$60 which was not too far away from the all-time high of $68.

Chipotle continued the inflation party long after the economy began signalling it needed a break and this ultimately came back to haunt them in 2025. In financial markets it only takes a few bad quarters for a story to “fall apart”. The first two quarters saw consecutive bouts of negative comparable sales. Counter narratives started forming. Margins begin to slide and so too did the share price.

If there is one thing you can count on, its the high correlation relationship between falling share prices and headlines declaring the end times for said company. In a lot of cases, this is apt. In some cases, and this is where you are paid as an investor, its a simple case of narrative following price. In the case of Chipotle, it is my opinion that the challenges facing the company are temporal. Nature catching up with a company that overreached in price without an accompanying increase in quality. Nature eventually striking down those who traded on borrowed time. We’ve since seen Chipotle make a strong effort to bring value back to the menu with incredibly low priced, protein packed, offerings. Smaller tacos, protein bowls with 32g protein under $4. It’s not exactly my cup of tea, but it’s an obvious boon to the add-on business as well as something to satiate the cheapskates.

In my mind, it doesn’t take a lot to put Chipotle back on track. In my opinion it never really derailed, but in the eyes of the fickle analysts, it has. Chipotle has an incredibly efficient box-box scaling model, high margins that can take a punch or two, and a largely untapped global market outside of the United States, where more than 95% of their stores are located.

Following the intra-day dump of Chipotle on October 30th, I picked up shares for the price of $30 a piece. I find it laughable that commenters claim that Chipotle is finished. Like there is not a world outside of the borders of the U.S of A. I don’t expect much in the 2025 fiscal year results. Revenue will grow at a subdued rate. Margins will likely contract. Comparable sales are going to decline for the first time since 2016. Much of this was priced in the second it became apparent to the market, many months back.

As for 2026, I see it probable that an improvement on 2025 results will occur. From there, I think the narrative will eventually shift back to business as normal. Maybe next year, maybe the one after that. Maybe the crowds shouting “Slop” will get bored and move onto the next struggling industry, who knows. I don’t invest on two-year time horizons. I am not skilled, nor lucky enough to do so. I have heard that longer time horizons improves the odds of getting lucky. Lord help me. At $30 per share, I think much of the downside is accounted for.

Thanks for reading,

Conor

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Thanks to my own motivation and the ‘Margins’ app (which helped add a sense of fun and accountability to tracking books), the habit is back. With such a congested schedule, I had to make time for reading again. I now spend the first hour of the day with a cup of coffee and uninterrupted reading. I also invested in a night-light to read in bed. In total, I set a goal of 10 books and ended up reading 13.

This year, I discovered that I get most enthusiastic about reading a book when it’s a mixture of narrative-based storytelling and non-fiction history. I find authors who fail at storytelling incessantly boring. Humans resonate most with great stories, so this is not surprising.

Below, I have compiled a brief overview of the books I read with my two cents on each. This is highly subjective, and the rating reflects my own personal taste.

If you have any recommendations you think I would enjoy, please comment at the bottom of this article. I also have a thread from Twitter I used as a source to stock my bookshelf; the replies in this thread have some excellent book ideas. I highly recommend checking it out.

Bangers-Only

5-Star Reads

These are the books that most captured my imagination and attention. For a book to be 5 stars, it has to capture that feeling of “I can’t put this thing down”. Those books that you reach for whenever you have a spare 30 minutes.

Red Notice (Bill Browder)

In December, I had a long-haul flight to India to catch, which required being in the air for ~12 hours. I destroyed this book during the flight, reading it in a single sitting. It’s more than 400 pages long… I think this was the most ‘addictive’ book I read all year. It was the first time in my life I’d read such a long book in one go.

It follows the personal account of Bill Browder’s journey of setting up a hedge fund in the post-Soviet era of Russia. As waves of countries ditched the communist regime and opened up their companies to private investors, Browder capitalised on these markets, offering newly minted public shares at inexplicably bargain prices. After incredible success, he soon stumbles into the dirty underbelly of Russia and its underhanded oligarchs. Things get crazy. Fast. This has everything from high finance to drama, and even murder.

Chip War (Chris Miller)

Embarassingly, i’ve never explored semiconductors in much detail. However, given their increasing importance in the world (a trend which kicked off many decades ago), I decided it was time to give myself a foundational lesson in the subject. Chip War does exactly that, walking through the history of the semiconductor industry, which started in the 1940s, and documenting its development from military to consumer application.

Throughout, the author excellently details the rivalries which ensue both on a corporate and geopolitical scale and how the dominance of certain players ebbed and flowed over time. It truly makes you appreciate the gravitas and importance of this technology, and would be a strong book for semiconductor novices and experts alike.

Apple in China (Patrick McGee)

After reading Chip War, I found myself having an itch for China (a nation that is discussed heavily in the book). Apple in China scratched that itch well. The book documents the relationship between Apple and the Red State.

How Apple leveraged China’s incredible platform for mass production in its earlier years to dominate the technology industry. Also, how, in later years, after China had been so welcoming to Apple, it revealed its claws to ensure that Apple, now essentially trapped in a dependent relationship, would struggle to escape. Apple in China is a great narrative-driven work of non-fiction, which provides a newfound respect for Apple’s secret sauce in supply chain excellence. In addition to the risks they knowingly took to develop it.

1929 (Andrew Sorkin)

This book, which I read in October, recaptured my love of narrative-centric non-fiction. If the author is not careful, they can make tantalizingly exciting moments in history feel drab and dull. I am reading a book at the moment called ‘The Asian Financial Crisis’ by Russell Napier, and it’s a slog because it’s so boringly written. 1929 is the polar opposite. It’s a dense, but light-reading and depiction of life amongst America’s top financiers leading up to and after the 1929 crisis.

This book made me buy a reading light because I was so eager to turn its pages that I developed a habit of reading before bed. Sorkin’s incredibly detailed research for this book is evident throughout. At the time of reading, it was interesting (and eerie) to notice similarities between the mid-1920s and today.

Buffet & Munger Unscripted (Alex Morris)

I’ve read a few Buffett books in my time, but I had never read ‘The Essays of Warren Buffett’ or similar texts that compile the oracle’s lessons via Berkshire shareholder meeting transcripts. That is effectively what Alex has done here, but the structure, organisation, and format of this compilation are superb.

While I can’t speak to others’ variations of this book’s contents, I felt that Alex has written an instant classic with Unscripted. The most up-to-date and expertly crafted curation of Buffett and Munger’s wisdom is found between the hardback confines of this book. I read this book in April, as I embarked on a month-long trip to India and Thailand. I have particularly fond memories of casually progressing through the book on the shores of Ko Samui, ice-cold coconut water in hand.

How the Scots Invented the Modern World (Arthur Herman)

Two figures whom I respect greatly had recommended this book, my father-in-law and the late Charlie Munger. I now understand why. As a Scot myself, one who was previously ignorant of my cultural heritage, I was interested to learn more. The Scots’ impact on the modern world and the incarnation of what is now the United States and Canada is incredible.

The book documents how Scotland, once one of the most poverty-stricken nations in the Western World, became the epicentre of the world’s greatest minds. While that period of Scottish dominance is certainly over, its impact and influence still have a strong standing today.

Enjoyable Reads

4+ Star Reads

These are the books that were enjoyable and that I would recommend to anyone. They just didn’t quite cut it for a 5-star.

High Growth Handbook (Elad Gil)

I kicked off the year with this book, after purchasing it from Stripe Press several years ago (check out their delightful website). It was the first book that Stripe Press published. If you are building software or working in a smaller company that is scaling, this book covers a good amount of breadth. I bought it to understand more about scaling a software company and the relationships between product, design, engineering, sales, and other various departments.

Littered with real-world examples and structured in a way that balances denser ‘textbook’ material with welcome interludes of frequent, thoughtful interviews. It’s one of those thick-looking books that takes less time to consume than expected.

When Genius Failed (Roger Lowenstein)

When Genius Failed is written by Roger Lowenstein, author of my favourite biography of Warren Buffett, The Making of an American Capitalist. He wrote WGF some five years later, in 2000, to tell the tale of Long-Term Capital Management. The fund, run by high-IQ academic-quantitative types, enjoyed a relatively short period of immense success that coincided with such favourable moments in the market as the Russian Debt Default, Asian Financial Crisis, and the Tech Bubble.

The secret ingredient to their destruction? Insane amounts of leverage and bravado. Icarus would be proud of this story. It’s a page turner, albeit a little meandering at times, but if you like details, this book covers the 5-6 year period of LTCM very well.

Expectations Investing (Michael Mauboussin and Alfred Rappaport)

There is an adage that being a great business analyst is not the same as being a great security analyst. Unique disciplines, both of which ought to be studied. I enjoy reading about how Mauboussin shines a light on the thread between fundamentals, price action, and expectations. In theory, it’s an incredibly rational way to invest.

Regardless of one’s chosen investment style, I believe this book belongs in the hands of any investor. It has a lot of replay value. The authors do some admirable work to interview real-life case studies between the academic nature of the content… which at times can be rather drab to read. I chose to read this while on holiday in the South of France. I don’t think it was the right vibe to marry my trip… but it was enjoyable all the same. I wish I had read this book when I was 18 and starting out.

Factfulness (Hans Rosling)

Factfulness was a book gifted to me a few years ago during a trip to India. I finally got around to reading it, and it was enjoyable. In a nutshell, this book stands to remind the reader that the world is actually becoming a better place, despite what you may read in the news. In a world with an endless supply of information, the author highlights the importance of focusing on facts, not narratives. If you actually study the facts, you will most often discover that the world, on the whole, is becoming a better place over time.

This book could be summarised into a short PDF of a handful of pages. Nonetheless, it’s a very easy and quick read, which I finished in a couple of sittings. It also makes you feel a little bit more optimistic about humanity, which I think a lot of people need these days. I would recommend this to the ignorant or easily convinced people in your life.

The Luxury Strategy (JN Kapferer and V Bastien)

The luxury strategy is a must-read for anyone involved or interested in the luxury space. Whether you are interested in fashion, design, investing, or business strategy, there is something important to be learned here. There is an incredible amount of misunderstanding about the word “luxury”, both from an investment and a consumer perspective.

I fully appreciate the perspective that luxury is a fugazi, incepted to capitalise on psychological drivers of the aspirational and elitists of society. Yet, it works. It has worked since the dawn of commerce. Understanding exactly how it works is the fascinating journey this book takes you on. I will note, and this is partly why it was rated no higher than 4 stars, that the authors academically composed this book. As such, the authors don’t seem to care about readability. It’s occasionally convoluted, repetitive, verbose, and as though the authors swallowed a thesaurus, optimising for vocabulary breadth > readability. Content matter is superb. The writing style could be improved.

The Design of Everyday Things (Don Norman)

I discuss design and work alongside designers every day, and it fascinates me. I wanted to start learning the foundations and expand my knowledge in this area.

This did make me want to explore more design-related books. Not quite a page turner, one chapter did feel like a drag, but overall, a fun and interesting introduction to design. Contained more psychology and business conversation than I expected, which was a plus.

The Rest

<4 Star Reads

These are the books that I persevered with despite finding some difficulty in finishing them. None are books that I would recommend.

Inspired (Marty Cagan)

Thankfully, I only encountered one book that I would go so far as to say I did not enjoy. This book was recommended to me by a colleague, and I would describe it as being “unseasoned chicken and vegetables”. It provides needed nutrients, but does so in a mundane and flavourless way.

I picked this up, looking to understand my role as a product manager some more. However, I found Inspired to be somewhat more suited to a new entrant to the subject. For someone aspiring to work in product or perhaps a student, this may be a useful resource. For someone who has already worked with product for years, I believe there are far superior books than Cagan’s. The content matter is solid, but the delivery is flat and incredibly boring. I found myself reading anything else but this to satiate my appetite.

Thanks for reading,

Conor

In a professional capacity, it means I have the entire morning to myself. I still wake at 6:30am as usual, but now spend the first hour of my day sitting on a balcony sipping coffee and conversing as the sun rises. I then typically read for a while, exercise, and have several hours head start on the day to get some work done. The downside is that now the ‘busy’ portion of my day happens between 6pm and 11pm.

From an investment perspective, I have seldom been one to care much about time sensitivity. During earnings season, I often skim-read the announcements the day they occur and circle back for a closer examination days, sometimes weeks, later. Moreover, the market's open hours no longer coincide with the central part of my day. Thus, being a little more disconnected doesn’t hurt.

I woke up this morning to flick through the Federal Reserve December meeting (which occurred as I slept soundly). As I concluded, I couldn’t help but feel a regime shift is underway.

From QE to QT

In Q1 2020, at the outset of the pandemic, the Federal Reserve reacted quickly by lowering borrowing costs and stimulating an economy that risked grinding to a halt. The rate was promptly slashed 50bps from 1.75% to 1.25% in early March. Just weeks later, the rate was cut by 100bps to 0.25%, where it would remain until February 2022. Coinciding with this decline in borrowing costs was a monumental bout of quantitative easing (QE). The Reserve pulled out its cash bazooka and started buying.

From March 2020 to its peak in April 2022, the Federal Reserve’s balance sheet swelled to more than double its size, growing from $4.1 trillion to just shy of $9 trillion. The situation was so bizarre that in 2020, the Reserve used a legal workaround to purchase corporate bond ETFs. Between the 12th May and 17th June, some $6.8 billion was used to purchase a mixture of investment-grade and high-yield (aka, Junk) bond ETFs.

As the panic subsided, life gradually became ‘normal’ again, and markets settled. The Fed would put an end to the QE cycle in March 2022 by conducting a 25bps rate hike and ceasing to be a net purchaser of assets. It was now time for quantitative tightening (QT). Thanks to an unwelcome side effect of explosive stimulus and a recovery boom in consumption, inflation started to infect the economy. In retaliation, rates would climb at a fast clip, climaxing at 5.50% in 2023, and the balance sheet would become $2.4 trillion lighter (27% down from peak).

Examine the chart below, which displays the Federal Reserve balance sheet, the level of the S&P 500, and the Federal Funds Rate since 2020. You can bear witness to the striking correlation between the Fed’s actions and the S&P 500.

The onset of the pandemic saw the S&P 500 tumble more than 30% in the space of a month. Precisely at the time the Fed unholstered its arsenal of financial weapons, the index, seemingly unperturbed about the state of the world, climbed out of the trough and aggressively marched forward. By August 2020, the 30% drop in March was erased. The fastest retracement in history. A recovery that had far more to do with liquidity than fundamentals.

By December 2021, the S&P 500 was up 120% from its lows and ~45% above its level before the pandemic started. Then the Fed began to indicate that it was time for rates to climb again in 2022. The market drifted downwards over most of 2022 as the Fed’s signalling became reality, falling 25% from highs as rates surpassed 3%.

To this day, there are industries still feeling the hangover of the turbulence in supply and demand dynamics from the pandemic. Yet, by 2024, the economic situation looked relatively stable once again. Inflation, which peaked at 9.10% in June 2022, was back in the 3% range. Unemployment had gradually declined from the pandemic highs of 14.70% in 2020 and was now oscillating around the mid 3% range. Corporate earnings had turned a corner, and the semiconductor and AI narrative had begun to sweep across markets, concocting Wall Street’s latest distraction. After declining by 18% in 2022, the S&P 500 recorded annual returns of 26% and 25% in 2023 and 2024, respectively. By the time that President Donald Trump reminded markets of his recurring tariff fetish in February 2025, it was as though the pandemic was long forgotten. There was a new panic in town.

Something That Rhymes with QE

Fast forward to December 2025. Rates had been declining for well over a year as the Fed continued to reduce the size of its balance sheet. Just last night, on December 10th, the Reserve announced a further 25bps cut, taking the rate to 3.75%. Within the press release, the Summary of Economic Projections (SEP)2 depicts more modest rate cuts going forward with a median of 3.4% in 2026, 3.1% by 2027, and 3.0% in 2028. But notably, they did not commit to further cuts, stating they will “carefully assess incoming data”.

More interestingly, the statement remarked “The Committee judges that reserve balances have declined to ample levels and will initiate purchases of shorter-term Treasury securities as needed to maintain an ample supply of reserves on an ongoing basis”.

This translates to the Fed saying that the balance sheet is unlikely to shrink in the near term. The agenda of QT appears to be concluded for this cycle. While the intention to resume purchases of shorter-term treasuries nods to the easing of financial conditions, it’s not quite easing in the quantitative sense. It’s not a shift from shrinking to growing the balance sheet. It’s a shift from shrinking to maintaining the balance sheet. Stabilisation, not stimulus.

This may give the Reserve some time to assess what the economy needs. In the release, they alluded to persistent uncertainty about the near-term outlook.

“Available indicators suggest that economic activity has been expanding at a moderate pace. Job gains have slowed this year, and the unemployment rate has edged up through September. More recent indicators are consistent with these developments. Inflation has moved up since earlier in the year and remains somewhat elevated. Uncertainty about the economic outlook remains elevated”.

It’s not unreasonable to assume that the Reserve will resume QE should the economy deteriorate further.

1. First QT slows

2. Then QT stops

3. Next, purchasing short-term treasuries to stabilise

4. Perhaps a few more rate cuts to follow

5. Economy worsens ➝ Resume QE

But what if the economy somehow improves?

I can confidently attest to having no idea. I don’t have data that stretches back far enough. Nor do I have the first-hand experience. I was raised in a post-GFC era, where the rules changed forever.

The same dynamic between the central bank balance sheet and interest rates was not present during the GFC. From 2007 into early 2008, the Fed gradually expanded its balance sheet while cutting rates to practically nothing. Then, when the financial system collapsed in late 2008, the balance sheet went vertical, more than doubling within months. There were small bouts of balance sheet reduction in 2010, 2011, and 2012 that coincided with declines in the S&P 500, but rates remained fixed at 0.25% for half of that decade.

The next time the Fed downsized was at the end of 2017, while rates gradually increased to 2.5% by the summer of 2019. By August of that year, the Reserve began to ease. Assets climbed 10% by February 2020 in response to the repo crisis. Meanwhile, rates had fallen to 1.75%.

You could argue a resemblance to today in this period. The QT slows and stops by 2019. A few rate cuts come, QE resumes. But then an anomaly arrived (the pandemic), and we never got to see how this would have played out because the Reserve had to react to a different fire.

New Chapter

The Fed has signalled it will stop reducing its balance sheet, but this doesn’t mean that QE is upon us. I’ve witnessed a lot of commentary indicating that we are not far away from a repeat of the 2020 QE cycle, and this will be a huge boon to stocks. While I have learned to never say never in the stock market, I am confident that if this were to happen, it would not do so on the same scale. Moreover, I can’t help thinking that this is an act of recency bias.

I am more comfortable acknowledging I have no idea what will unfold in the near term, but that we are now entering a new chapter in financial history. For all the analogies I could muster, we are still living in a monetary regime without a great deal of precedent.

Thanks for reading,

Conor

1

Rate my set-up… No longer with my dual-screens, I find a simple desk and Mac set-up to be refreshing.

2

SEP Table.

Now and then, a Twitter thread will be dusted off from the warehouse of some exuberant period in financial markets. The thread usually contains a bunch of stocks that have performed terribly since that date. People point, laugh, say “What a sign of the times” and move on. One of the most visceral examples is the time Brian Feroldi asked Twitter, at the peak of 2021 mania; “What company is worth less than $10 billion today but you think could be worth $500+ billion in a few decades?”. He aggregated the top 20 responses and it is fair to say those picks were dreadful.

- Me, August 26th 2024

Since that infamous thread of future “$500+ billion” companies was posted, the basket has lost 61% in value while the S&P 500 has compounded at 12.5% per year, grossing 67% in returns.

Anyway… this letter culminated in an attempt to create a crowdsourced basket of ideas that “doesn’t suck”. To my surprise, we achieved it. So I think it’s about time we rebalanced this portfolio with new submissions.

The ideas were crowdsourced from readers of this newsletter. The T&C’s1 were defined, a start date2 was set, and I gave you each a week to submit your suggestions.

In total, 39 unique companies were submitted. Companies with more than 1 vote would command a proportionately higher weighting in the starting allocations. This was the case with popular suggestions like Amazon (8.43% starting weight) and Palantir (6.25% starting weight). Below, I have created a table of each holding, the absolute fluctuation in weight from inception to the 27th November 2025, and the individual returns of each stock over the period.

There was no official benchmark for this portfolio, but given that investing in an S&P 500 ETF would be the laziest way to manage one’s money, I will hereby knight the benchmark of this experiment as so. There is a matter of some minor differences in geographic exposure3, but we’ll let that slide. Compared to the benchmark’s 24.06% return over the lifetime of the Crowdsourced portfolio, just 12 (~31%) of the individual holdings outperformed. One pick in particular, Luminar Technologies, saw its share price plummet by 94.46%.

However, the stellar returns of Rocket Lab (+502.44%), Palantir (+421.62%), Cloudflare (+139.09%), Unity Software (+137.53%), Alphabet (+94.29%), and Tesla (+93.26%) resulted in a 25.37% surplus to the S&P 500 over the period, with the Crowdsourced portfolio generating returns of 49.43%.

For more details, I prepared a high-level report on the portfolio below. Feel free to read that.

Crowdsourced Portfolio Report

1.21MB ∙ PDF file

Download

A brief Report of the Crowdsourced portfolio vs. the S&P 500 over the lifetime.

Download

I want to put the investing acumen of Investment Talk readers to the test… again. I want you to try your hardest and avoid submitting ideas that are based solely on upside with little consideration for downside risk. Imagine someone asked you to put your entire net worth into a single stock for five years. You’d be more likely to base this opinion on stocks that will perform well but also have a low chance of taking you out of the game entirely.

To Participate:

• Comment below ONE equity you think has the greatest chance of beating the market, or performing amicably, over the next year or so.

  • Please include TICKER and NAME to avoid confusion.

T&C’s

I am going to leave this open for the next week or two. Once closed, I will aggregate the names and then create a rebalance for the existing model portfolio to track the performance over time.

• The portfolio will be limited to a maximum of 40 individual names.

• Funds or non-equity submissions will not be counted.

• Each mention of a ticker will count as 1 vote. Duplicate entries will earn more votes, thus increasing the likelihood they are selected for the top 40.

• If more than 40 names are suggested, the top 40 will be selected based on weight. If there are submissions with equal weights on the threshold, excluded submissions are at the discretion of the admin.

• The portfolio will maintain the inception date of August 26th, 2024.

• The portfolio will be rebalanced as per the votes on December 8th 2025, with no rebalancing or allocation changes thereafter.

• One entry per person, the first entry will be counted.

• The portfolio will use USD as the base currency.

Thanks for reading

Conor

3

Crowdsource vs. S&P geographic exposure, country

With the blood vessels in my face constricted and my nerve endings now forcefully awakened, I grab a portable lamp, my book, and a laptop and migrate to the kitchen. The first hour or so of my day is usually spent reading and drinking coffee. Some time passes.

As the last chapter of my reading time concludes, and the sun begins to illuminate the city through my kitchen window, I perch myself on the counter. Opening my MacBook, I discover that vast swathes of the internet are down. The culprit? Amazon Web Services. It’s the type of incident we’ve all experienced before. Within a day or two, it will all be over.

Later that morning, I was relieved to stumble across firm evidence that the world was steaming ahead as usual. While cloud service outages come and go, you can always count on politicians who lack a basic understanding of something to try and dictate how those things should work.

This time, it was the turn of US Senator Elizabeth Warren. “If a company can break the entire internet, they are too big. Period”, she proclaimed. Promptly followed up by her catchphrase, “It’s time to break up Big Tech”.

I won’t be wasting my breath explaining why this is a delusional take this morning. Rest assured, Elizabeth will reappear later in this text.

Statements like these are big, bold, and attention-grabbing. They make great headlines because they exert a magnetic attraction, sucking both sides of the peanut gallery into the centre with a calamitous BANG like protons in a Hadron Collider. The protons, in this case, are the vocal proponents and opponents to the proposed solution.

This comment from Senator Warren reminded me of something which occurred days earlier.

Browsing through the internet, I noticed an old high school friend shared a video of someone complaining about the cost-of-living crisis in the United Kingdom (UK). My curiosity got the better of me, and I watched it. The man who goes by the pseudonym “Tattooed Dave” complains that the energy companies are earning ‘record breaking profits’ in the wake of rising energy prices. Most ludicrously, he proceeds to single out Tesco, the largest supermarket in the UK by market share and sales.

“The ****ing supermarkets are making record breaking profits. Tesco could pay every one of their employees a £10,000 a year bonus. They would still make a profit”.

A few unfounded soundbites presented as “facts” and a couple of swear words later, the video ends. My brain cells begin the slow process of regeneration.

The video implies that Tesco is taking advantage of the UK consumer and is directly benefiting from the fragile and inflationary environment post-pandemic. We’ll get to why that isn’t true in a second, but this isn’t a phenomenon unique to the UK.

US Senator Elizabeth Warren (told you) has been vocal in her belief that US supermarkets are to blame. In a 2024 hearing, her opening statement claimed that “Grocery prices are up because of good old-fashioned corporate price gouging”. It’s true that, pretty much globally, grocery prices exploded during the pandemic, and in most cases, they’ve continued going up even though the pandemic is now behind us. Warren has a track record for spinning encapsulating headlines that lack nuance. It’s what sells newspapers and attracts the confirmation-bias-seeking crowd. The same goes for the other side, too, don’t get me wrong.

Seeing people I know, many of whom are smart and capable, share nonsensical information like this makes me contemplative. Why do so many people my age, young people, have such anti-private-sector views? Why do they so easily succumb to this narrative that capitalism is “bad”? There are cultural, educational, and structural reasons, all feeding off each other.

I don’t know the answer.

Perhaps it’s because the private sector is an easy scapegoat for politicians and the media to blame for the economy’s problems. Ironically, the sitting government appears to do everything in their power to squash the motivations and prosperity of private enterprises.

Part of it is education, or rather, the lack of it. It is estimated that as few as ~25% of UK adults actively invest in the stock market as of 2024, compared to more than 50% in the United States. It’s no secret that the citizens of the UK are relatively risk-averse compared to their American cousins. When you don’t own equities, you don’t see capitalism as your system. You see it as someone else’s.

With respect to household wealth, the US stands head and shoulders above the UK and EU, with ~35% of household financial assets devoted to listed equities, compared to 10% for the UK and Euro Area.

The culture around risk and aspiration in the UK is complicated. Ambition often feels like a character flaw. It can be likened to the famous ‘crabs in the bucket’ maxim, where anyone climbing becomes a target for being pulled back down. Pair that with low wages, swathes of red tape, and you have a culture that sneers at success instead of celebrating it.

One need only skim the headlines of the Financial Times to see the symptoms. Countless UK-listed companies are being snapped up on the cheap by American private equity, others shifting listings to New York, and CEOs quietly relocating for tax sanity. The message is clear: ambition enjoys a warmer climate elsewhere.

I’ve been reading Andrew Sorkin’s ‘1929: The Insider Story of the Greatest Crash in Wall Street History’. It recounts one of Winston Churchill’s visits to the States in 1929, where he noted that, unlike in Europe, “the social life of the United States is built around business”. It’s a sentiment that feels as true today as it did nearly a century ago. The UK still can’t decide whether it admires that or despises it. Some things never change.

I digress.

A lot of ordinary citizens find arguments like “Tesco are the bad guy” encapsulating. We can pontificate on exactly why. If you lack a basic understanding of finance, it becomes significantly easier to believe this at face value because the ability to exercise critical thinking towards the matter is absent. This is true for every complex subject matter.

Take the health and fitness industry as one example. The majority of the public is not versed in the disciplines that would provide a more critical lens through which to discern claims. They are not nutritionists, dieticians, biologists, and so on. They are prone to believing claims at face value. In the 70s and 80s, the in-vogue war cry of the health industry was that “fat is bad”. As the consensus shifted towards the reality that, in fact, not all “Fat” is bad, the stigma of the word “fat” still lingers decades later. Various other food groups have transformed from villains to superheroes over time. Eggs and their “link” to cholesterol being one.

It sounds unfair that these huge companies earn billions in profits while the average household is blighted by ever-increasing grocery costs.

Big Media know this, and capitalise on it. Despite knowing that absolute values tell a one-sided story, they push this narrative onto the public, which, now more than ever, lacks the desire to interpret headlines via critical thinking. In practice, this means they read the headline, consume the Short-form video or the soundbite, and they assess whether this confirms their prior beliefs. If it does, it becomes a new fact in their arsenal. If it doesn’t, they simply ignore it.

Rarely will someone explore the merits of the claim.

The ****ing supermarkets are making record breaking profits

Let’s now address Tattooed Dave’s claims that “The ****ing supermarkets are making record breaking profits”. I’ve seen this exact headline blasted across various news outlets before, so we can be assured that Dave picked up this argument from the media cycle and has decided to run with it. Due to a dwindling number of publicly traded large supermarkets in the UK, and the fact that he singled them out, we can focus on Tesco.

Spoiler… the headline is false.

Tesco are enjoying record sales. The £69.9 billion the company generated in fiscal year 2025 represents an all-time high and a 2.5% increase on the prior year. Compared to the period ending February 2020 (Tesco’s fiscal 2020), the company’s sales have grown 8% after recovering from an 11% decline in the first year of the pandemic (Tesco’s fiscal 2021).

If we run our finger down the income statement and focus on operating income (EBIT), Tesco reported £3.1 billion in EBIT in the latest fiscal year (2025) with £2 billion in net income after interest and tax. This does reflect the highest earnings over the course of the current decade. But a glance at Tesco in the pre-scandal era of 2009 through 2012 (fiscal years) shows that this is by no means “record breaking profits”.

Tesco’s operating income and net income were higher than 2025 in 2009, 2010, 2011, and 2012, with the latter year representing the high-water mark that has remained unchallenged.

But here’s the catch. I tricked you (sorry). The numbers in the above table for fiscal year 2025 flatter Tesco, as they are adjusted to exclude certain non-recurring items such as restructuring, property write-downs, and expenses linked to the sale of Tesco Bank. The unadjusted numbers for the latest year are moderately worse. In the latest fiscal year, Tesco’s unadjusted EBIT was £2.7 billion with £1.6 billion in net income.

This puts to bed the first claim from Dave’s video. Tesco are not earning record breaking profits. But what about the second claim?

“Tesco could pay every one of their employees a £10,000 a year bonus. They would still make a profit”.

As per Tesco’s latest annual report, the company employed an average of 341,108 people in the fiscal year 2025. If Tesco paid 341,108 employees a bonus of £10,000, their balance sheet would be £3.4 billion lighter. In the real world, this payment would be an operating cost. Tesco’s £2.7 billion in operating income would not cover the cost, so the company would swing to an operating loss of £700 million before considering interest and tax.

Now they could use some of the £2.3 billion in cash they have sitting on the balance sheet, or the additional £2.2 billion in short-term liquid investments, but we’ll get into why that argument can be poo-poo’d shortly.

This firmly puts to bed the second claim from Dave’s video.

Reality called, it asked why you’ve not been around lately

There are certainly industries that are guilty of giving the consumer an unfair ride. My two cents are that the beauty of capitalism is that you don’t have to consume. If enough consumers vote this way with their wallets, or some new entrepreneur with a light bulb above their head decides to disrupt the market, the process of creative destruction should nudge the market’s invisible hand to do the bidding of the people. In hyper-regulated or statutory-monopoly industries, it’s not quite the same, but that’s not a facet of the supermarket industry.

We can delve into the semantics, examine industries that genuinely are malicious in their practices, but my point is this. Supermarkets are not the problem. They provide a vital service to the economy, utilising their economies of scale to offer produce and other inventory, sourced from across the world, at palatable prices. They employ hundreds of thousands of people in this country and others.

“But Waitrose and Marks & Spencer’s are so expensive”.

Don’t shop there then, go to Tesco. Go to Sainsbury’s, Asda, Lidl, Aldi, or one of the other great companies offering this service. Go to Amazon, shop online. I am not unsympathetic to the genuine struggle that inflation causes, but supermarkets, in particular, are as much a victim of inflation as the consumer. After expenses and taxes, a typical supermarket will earn ~5% operating margins. The net income margins will often be razor-thin, in the 1% to 3% range.

These margins continue to be low, despite passing on inflation to consumers during the post-pandemic inflation period. The practice of increasing prices to offset inflation has long been a common occurrence across most industries. It just happens to feel more painful when inflation is high.

Imagine for a moment that Tesco avoided increased prices to offset inflation since 2019. Their costs would still go up, as suppliers and other intermediaries passed their inflationary costs onto Tesco. The wage bill would continue to increase over time; avoiding doing so would have legal implications. Transportation, fuel, energy, packaging, all of these costs would creep higher still.

Tesco would eat the cost, and the net result would be operating losses. In plain English, Tesco would change from being a company that earns ~£0.05 for every £1 in sales, to one that loses money for every £1 in sales. That isn’t sustainable.

How does one plug the gap in the short term?

As we discussed earlier, when alluding to the imaginary £10k bonuses, Tesco could start to burn down some of the cash on their balance sheet and liquidate their short-term investments. This would naturally come at the expense of liquidity for other areas of their operations and stifle reinvestment into the business. Over time, Tesco would start to crumble as it struggles to exercise sufficient maintenance CapEx. In other words, it wouldn’t be able to afford to even ‘stand still’ as the rest of the market slowly moves forward.

What other options would they have?

The company could raise debt. Great, new cash flow. Now, how do they end up paying the interest and the principal on that debt if the company is deteriorating? Not a long-term solution. History is littered with examples of companies committing leverage-induced seppuku.

Okay Tesco. Think. What else?

They could take drastic action. Cut the dividend, shore up that cash outflow. Stop all reinvestment outflows. Start selling off assets, stores, and cutting the labour force. Conservation by consolidation. The irony of doing this, however, is that it erodes Tesco’s cost leadership advantage. As the company shrinks, the leverage they have over suppliers to source and purchase inventory at bulk discounts wanes. Their costs climb some more. Tesco ceases to be a big fish, and their ability to offer lower prices to consumers will all but vanish.

It’s a self-perpetuating doom cycle. Generally speaking, if a market/sector has high rates of competition, which I believe the UK supermarket does, this is good for consumers and tougher for businesses. If Tesco disappeared tomorrow, there would be considerably less competition in the supermarket industry. Fewer reasons to try to keep prices low to compete with Tesco.

Inflation is like a viscous web that seeps into every crevice and corner of the economy. Into our homes, our companies, our state of well-being. One can make the argument that the spotlight ought to be shone on the government, who decide the policies, and the central banks, which influence the cost of capital and the money supply. Of these three branches, government, private sector, and central banks, it would be fair and reasonable to say that all suffer because of inflation.

One could say the private sector inherits inflation, much like the consumer, not its architect. And yet, as ever, it’s the easy target.

Thanks for reading,

Conor

Transcript Summaries

Corporate transcripts are packed with critical information. But they are also verbose and full of ‘fluff’. A good summary should extract the vital information and discard said fluff. They should do this one task well, and they don’t require interactivity.

When embarking on this project, I observed how peers tackled this. There were a lot of examples to choose from (hence, table stakes). I noticed a lack of vision and understanding of what a user wants a summary to be. Most often, the summaries would whittle down a transcript into a handful of bullet points, which read more like a high-level earnings news highlight— “American Express reported $X.XX in EPS… Management suggested they are optimistic about YYYY”.

On the depth scale, the dial was turned all the way to ‘As little information as possible without the page being empty’. A typical earnings call transcript will take an avid reader ~20 minutes to read, while most ‘summaries’ I’ve seen out there take ~20 seconds. They optimise for extreme brevity. We took a slightly different approach, aiming for ~3 minutes to read.

We didn’t want them to be ‘as concise as possible’ at the expense of, you know, informing the reader. Instead, we focused on reorganising the important information into easier-to-consume chunks and removing the filler.

Every unique type of event (earnings call, M&A, special call, etc) dynamically takes on its own structure and formatting to organise the summary into segments that matter and are relevant to that particular event. In what is arguably the most diverse event type, earnings calls, the summary will adjust to centre around the individual qualities of a company. Sections may include KPI trend tables, geographic commentary, specific business segment results and commentary, risks, guidance, and a concise Q&A breakdown.

As a result, I believe these summaries are higher quality, balancing the verbosity of a full transcript vs. the lack of depth in providing a few bullets. I implore you to try a few and let me know what you think.

The reason we optimised for organisation over brevity is that we felt this is more aligned with the actual workflow. The problem users have is not that they want to consume an entire transcript in 20 seconds2 (which is not actually possible). The problem is that transcripts are conversations, and the critical information is buried amongst a large corpus of word salad. Extracting that critical information and presenting it legibly was the goal. And if that takes a few more minutes to read front to back, that’s fine.

While a seemingly simple3 user experience, transcript summaries are one example of how LLMs can be used to enhance an existing workflow. The user doesn’t necessarily care that this summary was created using an LLM. The important thing is that an LLM made this workflow possible and seamless. This is the theme I want to pick at a little more. Over time, I am gravitating towards the idea that incorporating AI into a product is less about slapping AI labels onto things and more about enhancing or creating new workflows.

LLM Workflows are Everywhere

The wide-scale adoption of LLMs has captured society’s attention. There is no doubt about that. As they endure their ‘hockey stick’ moment, part of what is so exciting is the vast potential in both consumer and enterprise applications. A huge portion of the world’s inhabitants have now tasted one of the most mundane applications of modern LLM use cases, the chat-based interface, through the likes of ChatGPT, Gemini, and others.

While it feels criminal to call this mundane when it still (to me at least) feels like magic, the reality is that people have become accustomed to this offering. We are getting past the phase of accepting suboptimal responses, and we expect them to be high quality. In November 2022, ChatGPT 3.5 was born, and the genie escaped the bottle. Five days later, it reached 1 million users. A couple of months later, it hit 100 million users. Today, the likes of OpenAI’s ChatGPT and Alphabet’s Gemini have monthly actives (MAUs) in the hundreds of millions. I am sure this moment in history will be documented for decades to come.

Thanks to the desire of gargantuan enterprises like Nvidia, Microsoft, Meta, Alphabet (and more) to pump capital into this space for fear of being a victim of the innovator’s dilemma, this product has already become somewhat of a commodity. It’s not incredibly expensive to the consumer, it’s widely available, and there are several institutions that develop and offer these frontier models in a consumer-friendly package (ChatGPT, Gemini, etc). There are thousands of enterprises building products that are essentially ‘wrappers’ on top of these models, too.

The latter is particularly exciting. As with most commodities, there is an oligopoly of firms supplying the raw materials, but the exciting part is the layer above in which those goods are transformed to create an unfathomable number of ‘new’ product offerings. It is those offerings which are so exciting.

We’ve already seen an abundance of ‘AI Helper’ style tools pop up in all of our favourite software. We’ve also witnessed early innings of how these models can be blended with hardware applications in cases like Meta’s ‘Ray-Ban Display’ glasses, which pair with a neural wristband, exploring the potential of the ‘next screen’ to displace smartphones.

I won’t pretend to have any insight into what this space looks like in ten years, but I am excited about what the world’s greatest minds come up with.

LLMs are Eating the World

Some time ago (2011), the phrase “software is eating the world” was coined by Marc Andreessen in a Wall Street Journal article. There, Marc was highlighting a trend that had already been underway for some time.

“We are in the middle of a dramatic and broad technological and economic shift in which software companies are poised to take over large swathes of the economy.”

In this article, he cited Netflix replacing Blockbuster, Amazon transforming retail, and software transforming mechanical vehicles into computers on wheels as early examples. It became the defining mantra of the 2010s. It feels like we are now seeing a similar theme, this time orchestrated by LLMs.

Today, I am going to be focusing on the financial space, but I suspect the ramifications on labour demand and consumption behaviours will reverberate throughout the global economy for years to come.

Customer support is a well-documented use case. Companies across all sectors and industries have already implemented LLM-powered support agents that essentially hook up to their internal knowledge base to solve common and simple user support cases. We did this at Koyfin over a year ago now. Here are a couple of examples, but there are many more.

1. Intuit (INTU) claimed they’ve seen a “15% reduction in contact rate in the past year” for their customer support desk after implementing GenAI4.

2. London Stock Exchange Group (LSEG) told investors that “More than 80% of customer queries are now resolved using AI customer support tools” in July5.

3. Lyft (LYFT) issued a press release in February 2025 suggesting that their “customer care AI assistant has reduced the average customer service resolution time by 87% and is resolving thousands of customer requests each day”.

Outside of directly replacing labour units in a one-for-one manner, you have to consider the argument that LLMs make a single unit of labour more efficient. Suppose it helps a developer ship 25% more code. Does that mean you now only need four developers instead of five? If product requirements and PRDs can be spun up in seconds with the help of co-pilots, does your organisation need so many product managers?

In a 2025 paper6, funded by Microsoft, the authors suggested that job titles such as interpreters and translators, historians, sales representatives, writers, authors, telephone operators, concierges, data scientists, models, and market research analysts (among others) were most at risk of displacement by AI.

I have no idea what ultimately comes of this, but I find it likely that both arguments will be true. Namely, that LLMs will make certain labour units more efficient, and that this will result in fewer units of labour being required for particular roles or functions. Similarly, I feel that efficiency gains are context-dependent. This idea of labour being replaced by technology is not exactly a new phenomenon.

I was watching a documentary about Cadbury’s (the chocolate maker) recently. In that documentary, they spoke with veterans of their Bournville production facility based in the UK. In 1878, the site employed ~200 workers. By 1899, the site had more than 2,600 employees. By the early 1900s, a village was formed7 to house employees.

“George Cadbury was a housing reformer interested in improving the living conditions of working people in addition to advancing working practises. Having built some houses for key workers, in 1895 he bought 120 acres near the works and began to build Bournville village”.

Bournville village was born. From thereon, the village developed into a community with its own shops, schools, playgrounds, colleges, and various other recreational facilities. It is thought that by the mid-20th century, the Bournville facility employed between 7,000 to 9,000 people. The veterans from the documentary reminisced about this period and talked about how this gradually came to an end as more machinery was introduced, displacing the need for thousands of workers. An older gentleman, being interviewed on the facility floor, looked around the room, noting that hundreds of workers would clock in and out of the building every day and that now it only requires a handful of bodies to ensure production runs smoothly.

This trend was accelerated in the 2010s after Cadbury was acquired by Mondelēz International, which sought to industrialise the plant further. Today, the plant employs some 1,000 people, and the village ceased to be ‘for employees only’ decades ago. Such is the cost of progress and efficiency.

I have no doubt the age of LLMs will cause mass disruption to the workforce as we know it today, but I am equally optimistic that we humans will figure out some other use for those idle hands in the long term. We have a knack for this, and history confirms as such. Nowhere will this workflow transformation be more visible or fiercely defended than in financial data.

LLM Workflows in the Financial Space

In the financial world, there are a small group of kingpins specialising in the realm of financial data. Companies such as London Stock Exchange Group (LSEG), Standard & Poor’s (SPGI), Factset (FDS), Bloomberg, and Morningstar (MORN). I will lazily refer to these companies as the ‘Big 5’. Between them, they carry a significant competitive advantage in the fact that they “own” and are the licensors of datasets covering, but not limited to, global ETFs, Mutual Funds, Equities, SMAs, Credit Ratings, Fixed Income Data, News and more8.

To use this data commercially, as a business, you likely have to go through at least one of these companies to license their data.

Focusing on the financial data & analytics market for a second, let’s say there are two levels. The base layer is the aforementioned companies. They own the data which powers the analytics. The layer above is the consumer or enterprise-facing platforms, which organise this data and present it in an appealing way for practical use. So that professional investors, advisors, and even retail investors can analyse markets, track portfolios, and so on.

The aforementioned companies also play in this space. Morningstar has Morningstar Direct, S&P has Capital IQ, Bloomberg has the Terminal, Factset has its version of the terminal, and LSEG has LSEG Workspace. This layer is also home to an abundance of other platforms that use the kingpin’s data. Examples include Quartr, Koyfin, TradingView, Ycharts, Fiscal AI, and many more. Some, like TIKR, are almost exclusively wrappers.

Others, such as Quartr, Koyfin, and Ycharts, have carved out niches in addition to serving a wider audience or have stitched together such a wide array of data from multiple vendors that they have less concentration risk. These companies offer tooling that does not exclusively resell vendor data at a lower price point. They provide value-added functionality such as portfolio analytics, integrations, reporting, and so on.

Fiscal AI is an interesting one because, on the face of it, they are a retail-focussed platform providing data on equities and funds, likely from ~3 big vendors. However, this particular company has taken steps to shed the handcuffs of the Big 5 and is now creating its own dataset. The first example is their innovative approach to Segment & KPI data. Instead of licensing, they collect it themselves. Which means they can now license it to others (Ycharts being one example, Perplexity being another).

More recently, they have made efforts to start collecting standard financial data from filings, displacing their need to license data from Capital IQ. A filing comes in, they scrape it using LLMs, they populate the data in their database, and this flows onto their platform. Fiscal AI is, in effect, an API business.

To simplify, think of it this way:

• Morningstar is in the Vendor business: They collect, aggregate, and clean data, store it in databases, and license it to other businesses.

• Koyfin is in the Value-Added Distributor business: They license data from several vendors and distinguish themselves by offering value-added services such as advanced visualisation, data transformation, analytics, and unique tooling.

• TIKR is in the Reseller business: They license data from vendors without much added value and resell it.

The important distinction here is that distributors and resellers don’t own the data. The equally important caveat, however, is that the industry isn’t quite so simple. Morningstar, Capital IQ, LSEG, Bloomberg, and the other vendors are rarely ever pure vendors.

Capital IQ, for example, is a vertically integrated data provider. They own the underlying data and the software layer which commercialises it. On top of that, it also relies (albeit to a significantly lesser extent than non-vendors) on third-party vendors for some of the data it licenses and includes in its platform. The same is true for Morningstar and LSEG.

What is interesting about Fiscal AI is that they, more than anyone, pose a direct threat to the likes of Standard and Poor’s Capital IQ. Fiscal AI is attempting to compete at both layers of the market, as a vertically-integrated vendor.

Competitive Advantage Narrative

The rise of LLMs has people questioning if this competitive advantage will hold for the Big 5, given that it is now easier to extract this information independently, both for consumers and for enterprises. Thus, bypassing the expensive licensing costs. In practical terms, this suggests the barriers to entry have declined. Fiscal AI is evidence of that trend. Initially starting life as a reseller, the company has since become a vendor.

As a product manager who is often in contact with data vendors, I have noticed a spike in start-ups aspiring to replicate this model. Many of which are using LLMs to extract data from filings to create a database of global financial metrics, which they can either use to create their own platform or sell to other platforms.

This theme appears to be puncturing the Big 4’s returns (excluding Bloomberg, which is not publicly traded). Since 2024, the companies have declined between 28% (in LSEG’s case) and 42% for Factset.

I suspect this is a great thing for the consumer. As Peter Thiel once said9, “competition is for losers”. There are most certainly other factors at play here. You can paint any narrative about historical price action that fits. Whatever the case, I find the argument to be slightly flawed.

Take LSEG as an example. It’s an incumbent. One of the criticisms of products like LSEG Workspace (and other ‘terminals’) is that they are slow to innovate and have UI that looks like it was etched into stone during the 1990s. They are often built on older technical infrastructure, making evolution slower. Contrary to that argument, Workspace actually looks modern with a modular interface. The same can’t be said for all platforms.

Anyway, LSEG has been talking about AI workflows for years. In their H1 2025 earnings call, they highlighted several initiatives ranging from agentic analytics, co-pilots, natural language search and data prompts, and AI-generated news.

LSEG’s CEO, David Schwimmer, has been vocal about how important these advancements are and takes a view of welcoming the technology shift. In his view, AI enhances, not replaces— “the future is AI integrated into a desktop, not AI replacing a desktop”.

He is referring to the idea that because AI lowers the barriers, it means the competitive advantages of LSEG (and other vendors) are at risk. In reality, cheaper alternatives have been available for decades. Nothing personifies this better than the ‘Bloomberg Killer’ idea.

Now and then, a tweet will go viral that either;

• A: Questions why Bloomberg hasn’t been replaced yet,

• B: Suggests [product X] will replace Bloomberg

• C: Claims it would be easy to build a Bloomberg killer

• D: Some mixture of the above

It almost always captures a lot of attention. The author is almost always entirely ignorant. Here’s the reality of the situation:

1. People don’t understand why Bloomberg is an institution: Bloomberg is like the Swiss Army Knife of markets on viagra and steroids. It does everything. It has a professional network effect. It provides niche datasets that nobody else provides. It is, in effect, not replaceable by some users because it’s a mission-critical software. Commonly, people look at Bloomberg and then compare it to Yahoo Finance and say something naive like “Yahoo has live stock quotes for free”. They are not serious people.

2. What is not happening: Bloomberg is not in the business of competing with retail platforms for mass market adoption. The price point alone is the greatest signal of that. Most cited ‘Bloomberg Killers’ are retail platforms. It’s apples to oranges.

3. What is happening: There is genuine displacement occurring for investors who use Bloomberg, but only use a fraction of the more basic capabilities of the Terminal. To give just one example, Financial Advisors. They can live without Bloomberg and substitute their needs with platforms like Factset, Koyfin, and Morningstar. Another example is Investor Relations departments, which could replace a terminal with Quartr. However, this is not a new trend.

Back to LSEG for a moment. David Schwimmer’s confidence is warranted. There are undoubtedly going to be a lot of great innovations in the retail space. LSEG are selling to the same people that the rest of the Big 5 are. Those companies are all incorporating LLMs into their workflows. So while it feels like groundbreaking stuff is happening, I sense that it’s more ‘business as usual’ for the most part. At least in the medium term.

During the H1 call, they were also asked about this theme of new entrants, to which Schwimmer expressed an opinion I largely agree with. It’s less about having a cool UI; the advantage still lies in the quality of data.

LSEG are not selling to 20-somethings with a $25k portfolio. That’s not their market. Any professional or serious investor cares about data quality, and that is the Big 5’s manifesto. They own it, they have large quality assurance teams to maintain it, and they provide estimates and other proprietary data. The question from the call reads as follows:

“There’s been some worry in the market about that as a sort of disruption risks in workflow to the industry as a whole from sort of new fintech AI platform”.

Schwimmer’s response, which I will largely leave un-edited, reinforces the idea that professionals care most about data quality, availability and, importantly, auditability. These less price-sensitive customers want the best.

“You can have a really cool user interface, but the quality of the product depends on the quality of the data. And we have the broadest, the deepest, the highest quality data sets. The second point I would make is that users don’t want just a sophisticated -- I used this phrase before, sophisticated chatbot. They want that great AI functionality, and they want that AI functionality embedded in all of the other workflows. And that can be news curation, charting, order and execution management, analytics, risk systems. We provide all of that in our user interface, in Workspace. And we are building AI into all of that.

And so I think that’s a really important aspect of this in terms of -- again, you can have, as I said, sort of a cool user interface, but that on its own doesn’t get you there in terms of what our industry is looking for and what our industry expects. Our users also want that workflow and that AI capability to be interoperable with their enterprise workflow. And then the last point, I touched on this earlier, but the last point, I think you cannot emphasize enough is that users want data that they can trust and they can rely on. And so with respect to some of the new offerings that are out there, and we’ve seen and we’ve played with some of the flashy demos and other things. But in one of those in particular, that has gotten a lot of attention, if you go into their own press release, there’s -- that press release points to their -- there’s a link in that points to what they’re relying on and their accuracy in finance is at 51%. And their accuracy in market analysis, they don’t define what market analysis is, but I think we do a lot of market analysis. Their accuracy and market analysis is 14%.

So I think coming back to your question in terms of some of the fintech offerings, they may be cool and they may be fun to try out, but they cannot meet the demands of this sector, the demands of our customers today. And I think that’s really important to keep in mind.

We are embedding AI functionality in our offerings, and we’re certainly not sitting still. So I think -- and there’s more to come. So as I said before, I like our positioning. We welcome the tech innovation. We welcome the tech change.

Two of the biggest takeaways after reading this for me were the comment on the sophisticated chatbot and the importance of audibility, which is essentially the element of trust in the output.

When he said “users don’t want just a sophisticated chatbot”, this resonated with me. At Koyfin, we’ve been patient with how we incorporate LLMs into our platform, and only now do we have an exciting roadmap of features. I am grateful we were patient because we’ve had the advantage of learning from the mistakes of peers.

I will preface this next part with some admiration first.

Fiscal AI’s Evolution

I have enjoyed watching the trajectory of Fiscal AI (formerly Finchat, formerly Stratosphere). I have huge respect for Braden (Co-founder) and their team. They do a lot of things right, and it’s refreshing to see a business that ships fast, ships hard, and spends time on features they know users will love. While there is some intersection between users (i.e some users will directly compare Koyfin and Fiscal AI in a purchasing decision), I believe the goals of each company are quite removed. I won’t comment too much on that, but the intersection exists at the retail investor level. Where it differs is that Fiscal AI are an API business, and Koyfin have a growing market share in serving Advisors (an area Fiscal AI is not currently in).

To put it another way, the two companies are as likely to be competitors as they are partners10. Koyfin licenses high-quality data. Fiscal AI sell high-quality data to enterprises.

Admiration segment complete, one learning I have passively absorbed from Fiscal AI is that they learned that users don’t want a “sophisticated chatbot” the hard way.

Several years ago, Fiscal AI was called Stratosphere. Stratosphere was a reseller platform. Then one day, the same minds that built the Stratosphere created a beta application called Finchat.io, which was essentially an LLM wrapper come chatbot which plugged into Stratosphere’s data. This was incredibly novel at the time, I must say. While the two products were connected on the backend, they were two separate offerings. One day, around 2023, the team decided to merge the two and create Finchat.

Finchat would essentially rebrand the Stratosphere platform, make it look a lot cleaner and more terminal-like. Only now, the Co-Pilot (a rebranded version of Finchat.io) was the central feature on the platform. The co-pilot was a ‘do everything’ chat interface powered by LLMs and Fiscal AI’s data. It was an impressive feature, but I got the sense it was a jack of all trades, master of none. You could try to run a screener, generate a report, ask it questions about filings, and tell it to build tables. Yet, it was never clear what its superpower was.

Around a year later, the co-pilot, which was once the primary driver of the platform, was relegated to a left-hand-side navigation element. It became more of a ‘feature’ than a flagship staple of the platform. Then, in 2025, another rebrand came along. Finchat became Fiscal AI. In a press release statement, the company claimed:

“As we’ve grown, so have our ambitions — beyond the Chat interface. Fiscal.ai represents a bold new vision: to power modern financial data infrastructure through our Terminal and APIs, transforming how the world accesses and uses information in capital markets”.

Behind the scenes, the company was quietly planning to shelve the co-pilot. On August 19th, 2025, Braden would reply to a user on Twitter that “copilot is being retired soon”. As of today, the co-pilot no longer exists on the platform.

Braden shared the story on a podcast I listened to a few months back. There, he explained that they started to license the API for this co-pilot, it grew traction, and then stuttered as the churn rates were high. To their credit, they bit the bullet and moved forward quickly. I think this was a smart move on their part.

Where Fiscal’s co-pilot failed, I believe, is due to generalisation. It lacked a workflow-specific focus and was never quite good enough at any particular flow to warrant that desired stickiness. It was arguably better than ChatGPT at some flows, but not by a significant enough margin.

There needs to be some kind of super-intuitive and workflow-driven element to an LLM feature; otherwise, it just becomes a feature that tries to do too much at once. A sophisticated chatbot, as Schwimmer puts it.

Workflow Enhancement

Let’s use Quartr as an example, another player in this space I have a lot of admiration for. They introduced a chat interface feature (I know I just poo-poo’d this, but hear me out). The important difference, however, is how this product is marketed. From the get-go, it’s incredibly clear what this feature is for. It queries information from documents (filings, transcripts, press releases).

You ask questions, it searches the database and spits out a response. In the mind of the user, you have the expectation that it does this workflow well. Unlike Fiscal’s co-pilot, which had less of a defined use case, users won’t feel slighted by the fact that it doesn’t function as a charting tool or a screener, because it was never marketed as such. I have used Quartr’s document query engine, and it was a remarkably better experience.

These days, many investors are downloading transcripts and filings and dropping them into generic LLMs like ChatGPT or Notebook LLM. The obvious problem here is that (a) these LLMs are not tailored to this workflow and (b) they don’t sit on top of a structured database of the required data. In other words, you need to give them the data, then they analyse it. Quartr’s product is built on top of the data, meaning you don’t need to carry your digital briefcase of filings around with you. The irony here is that Fiscal’s co-pilot could perform the same kind of use case, and it was launched almost 2 years prior. I have no idea about the commercial success of Quartr’s product, but it felt like a solid feature when I used it. There was more of an intuitive moment of “oh, this is what this thing does”.

Takeaway

Over time, I am gravitating to the idea that LLM-enabled tools need to be built to enhance a workflow. Not starting from the LLM and saying, “How many different things can we make this do at once?”. Alternatively, they should create brand new workflows that were previously not possible. Genuine novelty, unlocking new patterns while avoiding the trap of confusing novelty for utility.

I am incorporating this belief as we work on the exciting roadmap we have at Koyfin. I’m dying to share what we are working on, but given that some are truly unique in nature, I will be keeping the wraps on it for now. But what I will say is that it plays into this idea that you should start with the workflow first, and imagine how LLMs enhance that… with a little extra.

Like any good product/feature, it should be intuitive and obvious what it does, and not require a ton of instructions and articles.

Thanks for reading,

Conor

This is the longest I have gone without sending a newsletter since I started this publication over five years ago— the last entry being in May. During this absence, I have been busy.

In my personal life, I spent a month in Asia, where I visited Thailand for the first time. When in Ko Samui, I decided it was about time I proposed to my partner. I also had the pleasure of visiting Northern Ireland for the first time. I can now say I have visited every country in the United Kingdom.

At Koyfin, the business and the team are growing, and i’ve never been more excited about our trajectory and the opportunity we have ahead of ourselves. It’s been eight months since I last reflected on what we have been up to, so today’s newsletter will centre around that.

Below is a variety of the things we have released at Koyfin in 2025, as well as some commentary on what is coming down the line.

1. Shipped ✅

Features and improvements we have shipped to users.

I never tire of the satisfaction that comes from marking a highly upvoted feature request from our community feature request forum as ‘Complete’. The ones that garner more than 100 upvotes are particularly pleasing. This year, we have knocked a few of those off the list— including desktop alerts (300 upvotes) and adding historic data to our Watchlist & Screener (200 upvotes). We are also weeks away from unveiling another, the Interactive Brokers integration (150 upvotes).

1.1 Desktop Alerts

Desktop Alerts had been highly requested for years. We initially launched alerts on Mobile in 2023, with limited functionality of only price alerts for US stocks and Press Releases. The wait is finally over, and I believe that we went above and beyond to deliver a robust v1 of desktop alerts.

When we decided to work on desktop alerts, we wanted to ensure that this would be a dramatic improvement to what we supported in mobile, and in a way that complemented our desktop platform. In our first release of desktop alerts functionality, we:

1. Expanded coverage to include global equities, ETFs, and Mutual Funds.

2. Broadened alert types to include price, technicals, valuation, and documents (press releases, news, filings, transcripts).

3. Added the ability to set notes on alerts.

4. Supported setting alerts on Watchlists and Portfolios.

5. Introduced a notifications side panel to see notifications triggered live throughout the day.

   1. This panel is also interactive and will direct you to the source of the notification, whether that be a transcript notification or a price graph.

6. Created an alerts management dashboard that will allow users to edit, pause, and delete their alerts, as well as search and sort through their existing alerts, or manage their notification settings.

Alerts can be created or accessed through the ‘My Alerts’ button that will now feature throughout the desktop platform. Notifications delivery is also supported via Email, Mobile, and In-App for Desktop. There is more we can do with alerts, but this has proved to be a great foundation.

1.2 Historic Data in Watchlist & Screener

The concept is a simple one. Previously, in Koyfin’s watchlists, screeners, market and scatter plot graphs, the biggest limitation was a lack of time series analysis. Despite having thousands of metrics to choose from, you were limited to a point-in-time perspective. As an example, you could add EBIT margin to a watchlist, but the choices you had were the latest Fiscal Year (FY), Fiscal Quarter (FQ) or Last Twelve Months (LTM).

This update changed all of that. We created a new structure for our data in the column selection, meaning that metrics now have subcategories for FQ and FY history, as well as Historic Averages.

In a Watchlist, this made it possible to present the historical years or quarters of EBIT margins, to see how the metric has evolved. These historic metrics are also available for use in custom formulas— as demonstrated below, I created a custom formula to show the difference, in basis points, between today’s margin and the 5Y average.

It doesn’t take much imagination to consider how greatly this improves the screener's usability, either. If I wanted to screen for companies that had reported negative EBIT margins for the last 5 fiscal years but have flipped to profitability in the last twelve months, this is now possible, whereas before it was not.

In areas like Market Scatter, users can now more readily visualise data on a time series basis. In the above example, I have plotted the current vs 5Y average EBIT margins of the Semiconductor industry and overlayed a linear regression line to observe which companies are reporting higher margins relative to history.

One of the joys of being a PM at Koyfin is getting to help build features that I, as a user, am passionate about. This was certainly one of those occasions.

We are not done with historic data yet, however. We are going to follow up by adding more, such as:

1. Historic Trailing Growth Rates: For example, the growth of revenue over the last 3 years, 5 years, 10 years, etc.

2. Historic YoY & QoQ Growth Rates: For example, the YoY growth of each quarter going back the last 3 years. This will be great for visualising acceleration and deceleration.

3. Historic Actuals, Estimates, and Surprises: See how consistently companies beat estimates.

1.3 Portfolios & Integrations

Koyfin is loved by individuals and bottom-up fundamental analysts. But we also specialise in solving problems for Advisors. Back in December 2024, I wrote about how focused we have been on this demographic and how far we had come. At that time, we unveiled a new Advisor tier in our pricing plans. We now have two plans, Advisor Core and Advisor Pro.

The pace has not slowed. Below is a hand-picked selection of evidence that we are shipping features advisors have asked us for.

1.3.1 Integrations

In December last year, we had just launched our maiden integration, Schwab Advisor Centre.

Since then, we’ve added support for Altruist, Black Diamond, TradePMR, Interactive Brokers, and Orion. Our next conquest will be Fidelity, which we hope to make available later this year.

1.3.2 Client Portfolios v2

Client Portfolios was a feature we developed to push forward Koyfin’s status as a Portfolio Management System (PMS)— designed to support thousands of portfolios and integrate with an advisor’s custodian or other PMS tools. This gives advisors an efficient and fast way to visualise exposures, the P/L of their client’s assets, and seamlessly generate reports.

In our first version of Client Portfolios, the structure was flat— meaning that all portfolios were on the same level. We’ve since introduced a three-tiered structure:

1. Households: Highest level, contains Portfolios and Accounts.

2. Portfolios: Mid-level, contains Accounts.

3. Account: The atomic level.

The flexibility this provides with respect to household management has been immensely positive. Advisors can now organise client investments logically, move accounts across portfolios and households, generate reports at any level, and view data rolled up into an aggregate or zoom in to a particular account.

We also introduced the concept of views to Client Portfolios, meaning that all tables now feature customizable columns and the ability to create a multitude of unique views.

1.3.3 Custom Report Pages

In keeping with the theme of enhancing our core spine of advisor functionality, Reports was another feature we announced late last year that we have continued to improve on. We’ve added a host of new exhibits to reports, in addition to transforming several of the exhibits from static to customizable.

We also took this theme of customisation a step further by developing what we call ‘Custom Report Pages’.

Custom Report Pages allow users to create branded content within their reports and are designed to help tell the firm's story, explain the investment approach, and add context or commentary to proposals.

Download a Sample Report

This includes a new library of customizable pages that includes team bios, the ability to add charts with commentary, feature cards for outlining investment principles or service offerings, and editorial pages to meet every other need you might have when creating a report.

1.3.4 Short/Leverage Model Portfolios

If you are an advisor who employs leverage or short strategies, then model portfolios that support this are a mission-critical need. This was a common request from advisors, and considering established players like Ycharts don’t offer this, we filled that void.

Behind the scenes, this was no small feat. It required altering the fabric of our model portfolio infrastructure and a lot of testing, but on the front end, it works seamlessly. Users can now enter allocation weights as negative values and/or express >100% gross exposure at the portfolio level.

The UI dynamically adjusts depending on whether the model is long-only or contains shorts/leverage. Performance will factor in shorts and leverage, even to the extent that a model can become ‘bankrupt’ if the conditions allow for it. Reports will also dynamically adjust to support the correct analysis of short and leveraged exposures in models.

1.3.5 PDF Statement Upload

Imagine you are an advisor and you want to prepare a client proposal report for a prospective client later in the week. This report will compare the proposed model you are offering them vs. their current portfolio. They send you a PDF brokerage statement of their current holdings.

At this point, what are your options? You have to replicate the client’s portfolio in order to create this comparative report. This includes the lots, quantities, and cost basis, and a lot of other tedious manual work. While this manual workflow is available in Koyfin, it’s made a lot easier with PDF Statement Upload.

Simply drop the PDF statement into the reader, give the Portfolio a name, sit back, and wait. The portfolio should be processed and created within 24 hours, and Koyfin will keep you notified of the progress (in-app and via email) every step of the way. When it’s ready, you can spin up a proposal report in seconds.

1.3.6 Portfolio Capacity Upgrades

Quite simply, we bumped the maximum capacity (number of holdings) of our model portfolios to 1,000 holdings and the capacity of My Portfolio and Client Portfolios from 400 to 2,000 holdings.

Naturally, there have been a plethora of smaller enhancements made this year, but these are the ones I am particularly proud of.

Thanks for reading,

Conor

Note I emphasise the term ‘average’ person. The average person has never read a 10-Q in their life, doesn’t appreciate the nuance of a footnote, doesn’t know what a discount or risk-free rate is, and probably has a limited understanding of what it means to own shares in a company. So in this context, it’s a pretty short hurdle. As it relates to my knowledge relative to the average investor— I am not making any such claim.

You like stocks, what ones should I buy?

For anyone in a similar boat, and I am assuming this relates to most of my readership, you have likely experienced, perhaps on several occasions, a friend or family member asking for your opinion or advice on the broad umbrella of finance and/or investing.

To the average person, when you work in finance or are known to have an interest in the area of investing, it doesn’t matter whether you work as a bank teller, an economist, in a fund, as an analyst, or are simply an individual investor. To them, you work or are interested in “finance” so you must know about everything from the price of wheat to the geopolitical trade tensions of the times, to what stocks to buy.

The nature of the questions can vary, ranging from advice on saving and personal finance to asking whether the price of a publicly traded security is a “buy or sell” at a given time. Other times it may be open-ended— “What stocks should I buy right now?”. In some cases it may be an inquisition into your thoughts on a matter— “what is going on with the US tariff situation?”. It may be a request for an understanding of basic concepts like “How do I buy stocks?” or “What is an ETF?”.

Advising friends and family is a lose-lose scenario

As a general rule, I view all such questions as a loaded gun. On the one hand, you presumably love or have affection for these people. Being educated about finance and investing is a marvellous thing, and to help someone along that curve instinctively feels good.

On the other hand, it can commonly be a lose-lose situation. Here are a few thoughts on why:

1. You are not a financial advisor, and advising on matters in which you are not qualified can be problematic1.

2. You don’t, and will likely never, understand the full nuance of a friend or family member’s financial situation, their risk tolerance, their goals, and so forth. What is right for you, is unlikely to be right for them.

3. You don’t have the time to continually update them on the changing landscape.

4. You don’t have time to update them with your thoughts on individual stocks as they change.

5. The outcome of anything you advise them to do will be attributed to you.

6. You are encouraging a reliance on advice instead of encouraging them to pursue their own path of education. They should learn to make these decisions for themself, and be accountable to themself.

7. The average person will typically not pursue a path where they are dedicated to furthering their understanding of investing beyond a certain point. I will discuss this more shortly.

8. Investing in single securities is hard, and to be frank your advice might be lousy.

This list is non-exhaustive, to say the least. So what is the solution? Add a suffix at the end of every sentence “Oh and by this way, this is not financial advice”?

A few years ago I was having drinks at a bar with some colleagues I used to work with. They work in finance and are what I’d refer to as casual observers— more knowledgable than the average person, but not dedicated in the sense they read filings or follow individual companies closely. The topic of conversation often shifts to investing. One evening I briefly described a few companies I liked and the reasons why. While not a serious conversation, and one that was said in passing, I had focussed on why I like them as businesses. I had not commented at any time about whether or not they were attractive stocks— other than saying something to the effect of “at the right price…”.

Unbeknownst to me, the next time we met up, one of the individuals had bought a stock I mentioned and said it was down 30% or so and then sold it. Besides the fact I would not have purchased said stock at said valuation, I can stomach a 30% drawdown. I think most seasoned, long-term, investors can. The average person can not.

There is a side of me that believes your actions are your responsibility. If you follow advice— or in this case mere commentary— blindly and act upon it then on your head be it. However, if you have an audience or there is even the slightest perception you know what you are talking about on a given matter, you have a responsibility to be cautious about what you say.

An intelligent investor will acknowledge the opinion of others as that— an opinion and not fact. The average person is not an intelligent investor. This is why I am careful when discussing individual stocks in this newsletter, on Twitter, or in person. I make the point of avoiding directional language, providing forecasts, and suggesting action. You never know who is reading.

At the end of the day, I am aware enough to appreciate that I am a student, not an expert. Someone who cares about their friends and family— or audience— should make sure to preface any commentary with similar admissions.

How should you handle requests for advice?

This article is partly my intention to share my thoughts on the matters discussed, but equally, I want to hear from others about how they handle this situation. If you have some thoughts, I invite you to leave a comment or shoot me an email.

As a blanket rule, I think questions related to directional outcomes such as what stocks to buy or where the price of gold will be in 6 months, should be shut down with a simple “you have to buy what is best for your situation” or “I don’t know”.

The irony is that only novices will ask such questions. Everything is dependent on the context but most people will never seek to educate themselves past the first peak of the Dunning-Kruger curve and this is why recommendations can be so dangerous— which alludes to what I said in reason 7 for why advising friends and family is a lose-lose scenario.

The average person will typically not pursue a path where they are dedicated to furthering their understanding of investing beyond a certain point.

Those who want to learn more

When you intend to develop independent skills in investing, you will naturally surpass the initial peak of ignorance and tumble into the valley of culture. Cultured in the sense that this is the point when you realise investing is not easy. At this point, you likely appreciate the frivolity of relying on the advice of others when it comes to selecting investments— so you won’t find these people asking you questions.

Those who don’t

For the rest, they will be quite happy learning a few terms and basics, and thereafter relying on the advice of others. This is a precarious relationship to have.

What is permissible?

There are times when friends and family ask questions that are relatively safe to respond to. These questions have less potential for harm. A personal example I can relate to is that of a family member, with children, who asked me some questions on the basics of investing and what vehicles were available in the UK to invest in, both for themself and their child.

Questions such as:

• What is a stock?

• What is an ETF and how is it different?

• Can you explain the costs related to investing?

• How do you buy these instruments?

• What vehicles are available to mitigate tax?

• Etc

Particularly in the UK, I feel more obliged and enthused to help, because the education and general awareness or enthusiasm for investing is so low. My approach here was to answer any question they had related to the basics of investing with thoughtful detail— what stocks are, what ETFs are, and how to identify the inherent costs of transactions. To provide an overview of what vehicles are available and how they differ (ISAs, SIPPs, General Accounts) on tax implications— but not to explicitly recommend any course of action. Candidly, I did steer them towards low-cost ETFs— warning that picking individual stocks is not something to be taken lightly when starting out.

All of this was said with the understanding that you can’t load years of nuance into someone’s head who is not going to undertake the same dedication as you— reading transcripts, filings, etc. With most fields, you have to learn the rules first before you can appreciate and understand the nuances and exceptions— or the ‘buts’. I wrote about this in 2022 in an article called ‘Investment Maxims Are Not One-Size-Fits-All’. I’ll share a quote from that to give you an idea of what I mean.

“Investment maxims possess a beautiful irony; a dichotomy between simplicity and complexity. Simplicity requires an incredible amount of hard work to accomplish and the knowledge to appreciate it. Because investment maxims are simple, the nuance is often overlooked. Not only are they misunderstood but they are also mistaken to be a one-size-fits-all solution to the stock market. What might be perfectly good advice to one, is not applicable to another.

The notion that “diversification is ignorance” could be a destructive piece of advice for a beginner. Failing to grasp the true meaning, they could assume this means simply owning fewer stocks. They may then construct a small basket of concentrated positions, all within the same factor, on the back of that newfound knowledge. Put differently, maxims like this require the knowledge to appreciate it. Have you ever been asked a question by someone less experienced than yourself to which you respond with a watered-down version of the answer? At the conclusion of that response, there is often a desire to add “buts” and “well in most cases”, and “well sometimes…”. There is a tail of caveats that can be overwhelming for someone who doesn’t yet have the base knowledge to fully absorb and/or understand them yet”.

So in this case, I followed up by recommending a series of books that would help form that prerequisite foundation of knowledge— covering topics like passive vs. active investing, shorter books that cover particular themes from the ‘Little Book Of’ series, and some rudimentary books that answer the basic questions that most new investors have like “what is a stock and why do they go up and down”.

In conclusion, I believe that providing specific advice to friends and family is a lose-lose scenario and one that ought to be avoided. For queries that are more general, I think it’s fine to cautiously inform friends and family of the basics by answering their questions and recommending ways they can educate themselves— while avoiding directional or transactional advice.

But these are just my thoughts on the matter. I am curious, how have you handled this situation in your life?

Thanks for reading,

Conor

“Return, specifically the surplus generated relative to a chosen benchmark, is the ONLY barometer of success for an investor”.

Concentration Pays

That’s a polarising statement, isn’t it?

A few weeks ago, I stumbled upon a tweet from Mr Arny Trezzi, which has garnered 250,000 impressions (and counting). He pointed to his 403% return compared to the S&P 500’s 29% with an undercurrent of irony towards the fact he was unable to get a job at a hedge fund— it’s likely this performance decemates most hedge funds over this period. Naturally, I dove into the comments. To my delight, the comments were overwhelmingly positive (I was expecting a few “aCktUaLlLyY” reply-guys).

This tweet intrigued me, but I think some context is important to lay the groundwork for what I want to discuss. Paraphrasing Arny for a moment, this return was generated:

• From a start date of August 2023.

• Without leverage or options.

• By carefully picking individual stocks.

• Via considerable concentration (having been 100% long Palantir (PLTR) several times and for most of the period.

• Without the intention of selling courses or advice.

• Without regard for ‘traditional’ measures like Sharpe ratios, et al.

• With the acknowledgment that money managers can’t invest in this fashion.

For a longer breakdown, I implore you to read it straight from the horse’s mouth— here

I’ve spoken to Arny a couple of times over the years and am genuinely thrilled to see the success of his input. My perception of him is that he is bright, works incredibly hard, and doesn’t take himself too seriously. I think it’s evident that while he may appear to be exclusively focussed on a very limited number of stocks (one or two most of the time), he is a workhorse and loves what he does. Ultimately, an investor’s lessons are theirs to learn. One shouldn’t find oneself becoming too invested in the triumphs and failures of others. As Ralph Waldo Emerson once wrote, "Envy is the tax which all distinction must pay”.

I say this to preface that I am going to discuss other perspectives, and these perspectives are not necessarily my own, nor are they exclusively aimed at Arny’s situation. Rather, a broader discussion on returns, how someone might generate those returns, and our tendency to engage in comparison.

The cat who touched the stove

A perfectly natural exhibition of cynicism (or ‘realism’, depending on the stroke of your brush) would be to state, “Cool, try do that again”. The performance period spans less than two years, after all.

For every individual who made a killing shoving the stack into a stock at the right time, there are 99 who went all-in with the losing hand. Arny’s style is high-risk, high-reward, and it doesn’t require much imagination to conjure up arguments against his philosophy. By all means, single stock portfolios are less an impressive display of skill and more so an exhibition of courage, cojones and fortunate timing.

There is a parable about a cat that sat on a stove top. It goes something like this.

“A cat that sits on a hot stove will never sit on a hot stove again... but it will also never sit on a cold one”.

By my math, Arny’s CAGR at the time of the tweet was ~165%. Suppose he sold everything, allocated 100% to cash, and did nothing for a decade1. The CAGR would be 17% (before inflation)— a 700 bps surplus to the lifetime CAGR (10%) of the SPDR S&P 500 ETF, SPY.

But the cat that never sat on a hot stove before will continue sitting on the stove, assuming it will be cold, until the day it is not.

Not all trends are built the same

In the analysis of trends, I distinguish between fads (a moment), trends (a movement), and sustainable trends (trends with a second act). Concerning performance, you can think about it this way. A great short-term performance (say 0-2 years) is a fad— likely the result of luck or dominant market narratives or themes. You own a lot of energy stocks, which are in favour, and your portfolio does well.

A solid medium to longer-term performance (say 3-10 years) is a trend. Within this period, there is likely to be one or two cycles that have passed— with various factors and themes having their moment in the sun. Luck is less of an influence. If you come out the other side with a solid performance, then it’s more likely you have not simply got lucky playing the same hand repeatedly. There is an element of skill that has resulted in this return— whether that be in allocation, rebalancing, patience, opportunistic transactions, etc.

A strong long-term performance (10+ years) is a sustainable trend— although I dislike calling anything about investing sustainable because a lapse in judgement can come at any time. The idea here is that most investors with an aptitude can ride a bull market for a decade— a tide that lifts all boats. But it takes serious metal to endure several cycles, multiple bear-bull rotations, recessions, etc. The ‘second-act’ here refers to genuine skill and ability to generate excess returns during alternate regimes.

Compounded annual growth rates (CAGRs) are an incredibly effective way to measure and compare growth rates, but their utility is weak in the short term. Consider a start-up that generates $500,000 in sales in January. Someone then annualizes it to suggest they make $6 million this year. But if January was plumped-up by a one-time contract, the projection is misleading. Now, consider the S&P 500 did 10% in returns by January. Annualized, that’s well over 110%!

News flash: the index has never surpassed a 50% return in a calendar year. In stand-alone calendar years, it can be dangerous to place too heavy an importance on the S&P’s return. At the time of writing, the S&P 500 has returned 5.2% in the last year. Over the past 2 years, that’s 15.7%— 7.6% in 3 years, 8.4% in 4 years, 15.6% in 5 years, and so on. As the period observed gets longer, it gravitates towards the long-term average (10.04% over the lifetime of the SPY ETF).

An investor who earns a 15% return in a calendar year is not impressive. Nor is, in my opinion, an investor who earns a 150% return in a calendar year. A chimpanzee could do the same. Nonetheless, I bet it feels incredible (I wouldn’t know).

In 2024, in a piece called ‘Fads and Second Acts, ’ I wrote about the difference between short-term fads, longer-term trends, and sustainable trends. I’ll save you the reading and just share the conclusion.

“It’s important not to dismiss every trend as a fad. It’s equally important not to confuse every fad as a sustainable trend through extrapolation. It’s considerably more important to — take the time to ponder the difference between the two; identifying to the best of your ability which you may have stumbled across”.

This is all to say that we shouldn’t judge investors too harshly or praise them too heavily over short-term periods. That goes for shaunfreunde (revelling in the misery of others) and hubris (exaggerated pride or self-confidence in one’s abilities), too.

Hedge funds don’t work that way!

One commenter on Arny’s thread said the following:

“Hedge funds are about managing risk hence why it’s called hedge fund. What’s your sharpe and sortino ratios? What’s your max drawdown? What’s your factor risk exposure? What’s your idiosyncratic portfolio alpha vs. Systematic return?”.

Where to start….

I have a sense of appreciation for the response in some ways. It’s a common trope to question why money managers and/or financial advisors exist when “you can just buy the S&P 500 and pay no fees”. This sentiment misses the point entirely.

I think it’s a blessing to have such an interest in finance, money, and markets that you are willing to put your capital behind your ideas— to read the filings, read the transcripts, follow the footnotes, and what have you.

In reality, there is a tiny pool of people with a personality suited to this type of dedication. For many, whether it be a lack of time, interest, risk appetite, or education, offloading that burden to someone else— to use an advisor as an example— is a godsend. Advisors are not stock pickers by trade, but they help bring balance and structure to your finances through allocating funds, understanding your goals, tax planning, retirement planning, budgeting, cash flow planning, rebalancing, insurance, and a host of other services.

In short, an advisor’s fee is not a derivative of their ability to outperform the market. Nor is a hedge fund’s sole purpose to have the best performance known to man. They are certainly more geared towards outperformance than an advisor, and they are not merely tracking a benchmark like a mutual fund or an index fund, but they can provide access to more exotic instruments and generally have greater flexibility concerning how they invest.

What’s your sharpe and sortino ratios? What’s your max drawdown? What’s your factor risk exposure? What’s your idiosyncratic portfolio alpha vs. Systematic return?”.

To repeat the above comment once more highlights the bliss of being an individual. None of that shit really matters to an individual. Individuals cannot be compared to institutions.

Is Return the ONLY Measure of Success?

Circling back to the question that was provoked by Arny’s tweet. Is return the only measure of success?

It depends on who’s asking.

If you ask the populants of the world today “is the world getting better or worse?”, an incredible number of people will tell you the world is a worse place today than it was 30 years ago. In my opinion, these people are either morons or suffering from a tragic level of ignorance. As much as the media tries to persuade us otherwise, there has never been a greater time to be alive than today— this is factually correct when assessing the conclusion across most variables.

• The percentage of the global population living in extreme poverty today is 8.5% compared to 29% in 19952.

• The global female literacy rate has increased from 70% in 1995 to 84.1% in 2023.

• The global infant mortality rate has declined from 59.4 deaths per 1,000 children (5.94%) to 27.3 (2.73%) since 19953.

• The global life expectancy is now 73 years, up from 64 years in 1990.

• In 1995, just 1% of the population had internet access; today, it’s closer to 70%.

Global hunger rates, access to electricity and safe drinking water, aviation fatalities, child vaccinations, child labour… the list goes on. There are so many signs the world is a better place today.

Yet, with all that said, I can still understand why some people feel the world is not a better place. Most often, they base their assessment on some niche perspective that, within the context, justifies the answer of “no” to the question I proposed. The laws of mimesis show that humans tend to compare themselves to those closest to us. It’s why notions such as “relative poverty” exist and are legitimate.

In a similar vein, if you ask investors, “Is return the only measure of success?” there is an accurate and holistic answer. I believe that for the most part, the most accurate and convincing answer is “yes” if we change the word ‘only’ with the term ‘most important’— “Is return the most important measure of success?”.

Ultimately, investing is about taking your idle dollars and putting them to work in the hopes that they deliver returns. But returns relative to what? The question is open-ended. This is where the answer is not so straightforward.

• In excess of inflation: Every year, idle cash loses value thanks to inflation and currency devaluation. In other words, $100 today will purchase considerably less than $100 in 20 years.

• In excess of the ‘Market’: The ‘market’ is different things to different people. To some, it’s the MSCI World. To others, it’s the S&P 500. Whatever the case, if you could have earned more money, doing effectively nothing more than buying a passive ETF that tracks ‘the market’ then some will say your time has been wasted.

• In excess of the ‘Benchmark’: Some of you might say, “What is the difference between a benchmark and the market?”. We could argue semantics, but everyone’s version of ‘the market’ is a benchmark, but not every benchmark is someone’s version of ‘the market’.

• In excess of Everyone Else: To be ‘the best’ investor there ever was. A fine goal, as unrealistic as it may be.

Everyone has their version of what their returns are measured against. Whatever that is, the relative returns should be the most important measurement of success. If you are dedicating precious time towards this pursuit, then you should be validating whether that time was well spent. I think I have written about this extensively in the past, so I will spare the detour.

However, I think there is huge success in simply having the awareness to appreciate the potential life-enhancing force that investing can be, while at the same time demonstrating the respect and understanding that it’s not ‘free money’.

In a similar way that the Western world seldom appreciates the fact they have an abundance of clean drinking water, a ‘sophisticaed’ investor infrequently appreciates the fact they are already ahead of most of the population by having the wherewithal to prioritise their financial health.

From the perspective of a UK resident, the level of education and enthusiasm surrounding public markets are abysmal. The Office for National Statistics (ONS) reports that in the 2022/23 tax year, there were 12.4 million ISA accounts subscribed to in a country of ~45 million adults. An Individual Savings Account (ISA) is a tax-shielded investment wrapper that allows UK residents to invest up to £20,000 (~$26,000) per tax year, with all resulting capital gains and dividends exempt from tax, forever.

Of the 12.4 million accounts, 64% (7.9 million) were cash ISAs— an account that simply lets an individual earn tax-free interest on cash. Considering the UK has averaged 1.96% interest rates over the past 20 years, these individuals would have likely failed to circumvent inflation. Just 31% (3.8 million) of accounts were Stocks & Shares ISAs— an account that facilitates the purchasing of equities, ETFs, and funds protected from tax. In theory, a UK resident could max their stocks ISA each year and become a millionaire within 25 years, assuming a 7% annual return, and pay zero tax on that portfolio.

I’ll hazard a guess that 90% of my readers view the decision between utilizing the £20,000 annual allowance towards a stocks ISA and a cash ISA as a no-brainer. Yet, for most Britons, this isn’t the case.

It’s widely reported that more than 50% of American households own stocks directly. While harder to find a perfect comparative data set for the UK, the best estimate is between 20% to 25% for UK households. I therefore think it’s an incredible success for someone in the UK to get over their cultural risk adversity and real-estate-fetish and allocate money towards a stocks and shares ISA product.

As you become more competent in investing, naturally, you delve into alternate universes of comparison. We tend not to compare ourselves to people we consider ‘below’ us. Rather, those who are on roughly the same ‘level’ or slightly above us. When comparing your salary, you often look at people in similar job functions, of a similar age, and in the same country to gauge how fairly you are compensated.

Most new investors are not fixated on beating the S&P 500— they are more content with tracking the percentage of income they invest and learning how to invest. As time progresses, your base for comparison shifts. You beat the index— great. But you still didn’t beat Tom, Dick, and Harry who have outperformed you for years? Where does that pursuit end?

Ultimately, it’s the investor’s choice. There will be some who deny the idea that returns trump all. Picking stocks has so many other worldly benefits, such as education, community, and knowledge of the world. Then there are the more pragmatic of us who say no, a big brain doesn’t feed your family or lifestyle, being right does.

Success looks different depending on where you are in the journey and what your goals are. There is no right answer. There is an abundance of non-performance-related benefits that come from taking an interest in public markets, but at the end of the day, you have to have something to show for your efforts other than a bigger bookshelf and more interesting dinner conversation. There’s no shame in not beating the market. But there’s also no excuse for not trying4— at least, once you know what’s possible.

Thanks for reading,

Conor

My experience in the professional world is short. So too is my experience with life generally. As I approach thirty, I am grateful for the experiences I have been afforded and for the mentors I have had the benefit of learning from. Sometimes lessons come the old-fashioned way too, from books.

I have curated a few things I have been thinking about this year— some of which are broadly applicable and others specific to a product role that may not interest you. This isn’t career advice, nor will it apply to everyone. The common cliché of this type of material is that you write to your ‘younger’ self. In contrast, I view this as writing to my ‘older’ self. With any luck, I can look back on what I write today and cringe at how naive it was.

1. Mentorship

When I was younger, I often read that it was important to find a mentor—someone who could guide and advise you in all matters related to life and career. “Find a mentor”, people would say. “I am meeting with my mentor”, declared others. Due to my inexperience and the fact this concept was foreign to me at the time, I had preconceived notions of what this relationship should entail.

I imagined some kind of ‘search’ would take place— where you actively seek out your mentor and shape a formal relationship.

“Hello sir would you like to be my mentor?”.

“Of course, let me now mentor you, mentee”.

“Excellent”.

In retrospect, my view of mentorship was almost ceremonial— an affinity with a more experienced person that came with labels, scheduled meetings, and in a way a somewhat one-sided and transactional relationship. As I eventually encountered mentors, I discovered that none of this has to be true (at least, in my experience).

In reality, mentorship transpires organically and the symbiotic relationship between mentor and mentee often exists without vocal acknowledgement. Sometimes, you will stumble into mentorship as a result of proximity. Other times, you are a mentee from afar, learning from someone you admire without direct interaction— whether through their writing, talks or watching how they handle challenges, you can learn by observing and applying the lessons to your situation. If you are willing and eager to learn, a mentor will find you.

I once thought that a mentor was simply someone who demonstrated how to do things, gave you advice, and showed you ‘the ropes’— shaping you in their vision. What I found is a mentor is someone who identifies talents and capabilities within you that you may not have realised— giving you the freedom and trust to develop those abilities. Someone who identifies your potential and nurtures it.

I no longer believe the relationship to be one-sided. Benefits to the mentee centre around personal growth and skill development. Depending on the context, mentors can benefit by improving their leadership skills and improving the aptitudes of their employees. There is an element of reciprocal learning that occurs too— engaging with a mentee can fructify fresh thinking, novel ideas, and new perspectives.

As I progress in my career I consider myself fortunate to have had a couple of great mentors, both of whom took a chance on me and offered me opportunities to develop my skills in ways that would have been difficult in a more traditional career path. Mentors are all around us. You can learn from anyone, in any discipline.

2. The Single-Thread Leader

The single-thread leader is an organisation-design concept popularized by Amazon. While commonly applied to teams and groups, it’s a useful tool for the individual. This concept was taught to me in a previous role by a Product Manager I worked under. At the time, some responsibilities that had previously been handled by two people were being consolidated into a single owner— me. I was educated on the concept of single-thread leadership— used as a rationale for why this decision would result in higher agency and greater quality output.

There are many definitions, but I like this one1 from Pedro Del Gallego:

“A single-threaded leader is an individual wholly dedicated to solving one business problem, someone who wakes up in the morning and worries just about that one thing, ensuring the initiative’s vision and goals are always at the forefront and is ready to escalate risks early. Single-threaded leaders may be individual contributors, manage a single-threaded team, or a large organization whose attention is similarly focused on that one initiative. The defining characteristic is not the scope of the initiative but the single-threaded nature of the work”.

- Pedro Del Gallego

When a single person is fully accountable for an initiative or project, they have a stronger sense of ownership. They become more invested, make decisions that are more closely aligned with the success of the initiative and tend to drive more potent output because they are personally responsible for its success or failure. Accountability results in stronger engagement, higher quality work, and faster execution. The key point here is not that single-threaded leadership is about delegation— rather, it’s about licensing someone with responsibility, ownership mentality, and autonomy. When people feel a sense of ownership or responsibility, they care more.

“The best way to fail at inventing something is by making it somebody’s part-time job”.

- David Limp, Former SVP of Devices and Service at Amazon

I am sure many reading this can relate. We have all likely experienced a job where we feel like a replaceable cog in a giant machine. If one cog stops working (that’s you), another one can be put in its place at relatively short notice. Instilling a sense of autonomy into an employee is a smart decision for many reasons, especially because it makes them feel like an engine instead of a cog.

Cogs are replaceable, but engines propel the system. Cogs are mobilized from up above, engines mobilize the cogs. While this may not strictly be true in reality (even senior executives or CEOs are replaceable) it’s about how these individuals feel and engage with their responsibilities. It’s less fun to be told exactly what to do— it’s more fun to be told to go make something happen.

This concept relates to the next point— making yourself indispensable.

3. Make Yourself Indispensable

At face value, the term “make yourself indispensable” can conjure up a lot of different meanings. A simple way of putting it is that your absence will be felt if you suddenly disappear. This doesn’t have to mean becoming the master of the mundane. If a member of a packing facility steps off the line and goes home for the day, their absence will be felt— but the line member can be easily replaced.

So making yourself indispensable must be about making yourself irreplaceable? This is not necessarily true either— within reason almost anyone is replaceable given enough time. Becoming indispensable moreso aligns with the following non-exhaustive list;

• Developing a skill that few others in the organisation have

• Owning a function that nobody else does

• Being reliable and consistently delivering high-quality

• Taking the initiative to solve problems proactively

• Being responsive to solve retroactive problems

• Being a strong communicator

• The ability to learn and adapt quickly

• Willingness to take on more responsibility and ownership

Sometimes this means doing things you don’t necessarily want to, or that others don’t want to— or both (more on that later). The point is not to be thought of as irreplaceable (although, that is nice), but rather to create the impression that it would be a challenge to find someone to replace you— with the caveat that simultaneously nobody wants to replace you.

Ami Vora2 wrote a concise article about what makes an indispensable employee— one worthy of promotion. Get better at complexity, autonomy, and throughput:

Complexity: How difficult a problem can you solve? Sometimes this masquerades as “scope” or “breadth” or “depth” — all different ways to describe why a problem is hard.

Autonomy: Can you handle the problem with minimal guidance? This doesn’t mean “solve it yourself at all costs” — but instead, can you take the lead and pull in your manager and others appropriately to keep them informed or get their support when needed?

Throughput: How many hard problems can you solve at the same time?

- Ami Vora

4. Be Open to Doing Everything

Maybe this is a trope of being earlier in my career that I will someday realise outlives its usefulness, but I have always tried to be open to doing everything. Naturally, there are times when you should learn to say “No” or avoid doing work that is not an efficient use of your capacity— I imagine this is a more important consideration as seniority grows. But at my level, curiosity has allowed me to experience customer support, partnerships, social media work, and product-led work in addition to gaining insight into functions I don’t actively contribute to but that impact my role and organisation such as sales, engineering, marketing, and hiring.

There is an expression that the ‘jack of all trades is the master of none’ but I believe that understanding the various factions within an organisation will help in a stronger holistic sense of the organisation as a whole. This also feeds into the topic of perception vs. perspective, which I cover next. If you can’t “do” a function, take time to understand the position and what it entails from others in that role.

The concept of “trying everything” vs. “being a single thread leader” naturally collide. The conclusion is that “it depends”. Framed around context, career stage, and impact, each will be useful to an individual at varying moments in their life. Earlier stages in one’s career or tenure at a company are a good time to explore everything— later stages are conducive to specialization or deeper ownership. There are times when you must be a generalist and times when you should focus deeply on a limited number of objectives. The key is understanding when to say yes to learning vs. saying no to distractions.

5. Perception vs. Perspective

I have found the distinction between perception and perspective useful across a variety of workflows— whether in investment analysis, product-led work, or general communication.

Perception is the way that we each observe the world— “If there are 7 billion inhabitants of the earth, then there are 7 billion pairs of spectacles through which the world is viewed”3. Perspective is understanding how other people are observing the world.

In conversation, it’s often a battle of perception vs. perception. The sharing of perception unlocks perspective but this is seldom acted upon by those privy to the conversation. Perception tends to trap its owner in a narrow-minded frame of thought. The subtle shift in focus from perception to perspective when engaging in discussions can be powerful and arm you with an informational advantage.

In communication, it can lead to stronger arguments and persuasion if you understand what will resonate most. In decision-making and planning, it can help you pre-empt the pushback you may receive on a proposal and proactively augment the pitch or come up with rebuttals.

This is particularly true if your work involves communicating with technical members of a company— a point I address later. As a Product Manager, I don’t write code, I don’t know the language, and I don’t think I ever will. Yet, through conversing so often with engineers, who help me understand (amongst many things) our system infrastructure, I now often have a better sense of what the pushback or technical limitations of a proposed product requirement will be. This helps narrow the focus on the things we can deliver and avoids squandering precious product and design resources on functionality that extends beyond the realistic scope of the project.

In short, if you are a Product Manager, you shouldn’t always be thinking like a Product Manager. You should be viewing the situation from the perspective of the user, design, engineering, and various other stakeholders. The same idea can be applied to all disciplines. If, for example, you are a defence attorney, it helps to understand the perception of the prosecution.

6. Understand Your Influence Can Change

I’ve worked at companies with employee counts ranging from 30 to 2,000, to 100,000 with varying levels of influence. I discovered the potential and velocity to learn, gain responsibility, and evolve is levels of magnitude greater in a smaller company. I will add the caveat here that this is personal to my journey and the stage of my career. There are opportunities to excel at companies large and small.

In smaller companies, I have been fortunate to have some great mentors who supported my growth and for the first time gave me a sense of influence— responsibility to make decisions that affect the organisation. I will admit that I still find it somewhat weird when someone comes to me for a decision. I will add another caveat here that I am not overestimating the influence, as these decisions are largely product-related which, while important, can be rectified or changed.

To remain grounded, I remind myself that influence is subject to change. In Elad Gil’s book, the High Growth Handbook, he makes several great points about employees who scale and those who don’t. When a company grows from 100 to 1,000 employees the culture changes, and the CEO/founder should be the one communicating that culture transformation is okay and expected. What often happens is resistance to change.

I recall my first ‘real’ job out of university, working as a data jockey for an investment accounting software provider. The company at the time had ~1,500 employees and was a couple of years away from an IPO. Although I didn’t quite connect the dots as much as I can today, I recall there being a visceral divide between the ‘original’ employees and the swaths of new young graduates that flowed in as the company entered its scaling stage. The former clung to the culture that existed when the firm was considerably smaller. The latter embraced the new corporate identity of a company that was no longer founder-led.

Gil calls this the ‘Old-Timer’ syndrome of early employees4. The early employees who fail to understand that their influence will diminish as the company grows can become resentful, resistant to change, and will be outgrown by the company— constantly longing for the old days.

“Some of the most valuable long-term employees of a high-growth company join early on. These employees often have earned the trust and admiration of the founders and CEO, and they have the cultural context and long-term mission of the company in mind, which enables them to achieve outsized things in a high-growth startup.

Their "old timer" status allows them to challenge convention (or provide context on it) in ways that enable them to reshape or remove rules or old processes”.

- Elad Gil, High Growth Handbook

The employees that will thrive are those who accept their influence will diminish over the short to medium term.

“Early employees who are humble enough to realize they can learn from fresh blood can grow with the company and use it as a personal platform for their own learning and impact. Some early employees will stick with a breakout company for decades and their personal story arc mirrors that of the company. These employees tend to be hungry to learn from others, understand that the company, their role, and its culture will inevitably evolve, and are open to change.

A common sign that an old-timer will work out is their eventual acceptance that their role and influence at the company will shrink in the short- to medium-term as the team scales, but that it will expand with time as they continue to learn and the company continues to scale”.

- Elad Gil, High Growth Handbook

This is a facet I have not learned through experience yet, but one I am cognizant of so I can avoid slipping into the old-timer syndrome if the opportunity presents itself (see footnotes for warning signs).

7. Let Go of Things You Love Doing to Grow

Like the last point, this is another one I am expecting to learn through experience and am preparing for when the time comes. The idea of ‘Giving Away Your Legos’ was coined by Molly Graham5 in an article that shares the same name.

Graham witnessed the growth at Meta as it expanded from 500 to 5,500 employees in the early days. She describes the concept as follows:

“The best metaphor I have for scaling is building one of those huge, complex towers out of Legos. At first, everyone’s excited. Scaling a team is a privilege. Being inside a company that’s a rocket ship is really cool. There are so many Legos! You could build anything. At the beginning, as you start to scale, everyone has so many Legos to choose from — they’re doing 10 jobs — and they’re all part of building something important.

You have so many choices and things to build during this early phase that it’s easy to get overwhelmed. There’s too much work — too many Legos. You’re not sure you can do it all yourself. Soon, you decide you need help. So you start to add people. That’s when something funny happens on a personal level and to teams: People get nervous.

As you add people, you go through this roller coaster of, ‘Wait, is that new person taking my job? What if they don’t do it the right way? What if they’re better than me at it? What do I do now? These are some strong emotions, and even if they're predictable, they can be unnerving. In order to get to a really high-functioning, larger team, you have to help everyone get through this roller coaster. If you don’t, you can end up with a real mess”.

- Molly Graham, Give Away Your Legos

Until now, i’ve been focused on acquiring new skills and taking ownership of new responsibilities. I juggle several different functions, most of which I love, and I hope that someday I am forced to give away some of these functions— implying that the company and I are growing. There is a natural desire to want to cradle functions which were once your “baby” or to remain “in the details” as Airbnb’s Brian Chesky would say. But as Graham remarks, “Almost everything about scaling is counterintuitive”.

“One of the foremost examples is that reacting to the emotions you’re having as your team adds more people is usually a bad idea. Everyone’s first instinct is to grab back the Legos that the new kid took — to fight them for that part of the tower or to micromanage the way they’re building the tower. But the best way to manage scaling (and one of the secrets to succeeding in a rapidly growing company) is to ignore those instincts, and go find a bigger and better Lego tower to build. Chances are if you pick your head up and look around, there’s a brand new exciting pile of Legos sitting right next to you.”

- Molly Graham, Give Away Your Legos

8. Speak to Technical People

If you are not a technical person and you work with a technical product, speak to technical people. This is a mutually beneficial relationship. Engineers are the architects of your product but are not usually the target users. Conversely, a product person is closer to the target user and (should) have a desire to understand the infrastructure of the product they help cultivate.

Product people want big and powerful features. Design wants intuitive flows, continuity, visual feedback, and signifiers that make sense to the user. Engineering wants to maintain a strong cadence of delivering new features and improvements to production, efficiency, an absence of bugs, and happy users.

Earlier in my career I asked why don’t companies just hire product people who can code, or engineers who are gifted with great product sense? In reality, while it’s certainly possible to find some instances of this, it’s not the norm. They are different mental mappings. As a product person, communicate with engineers as much as possible. Don’t accept an explanation, seek to understand it.

This takes time, numerous conversations, and repeated exposure, but if you absorb as much as you can, you will further your understanding of how the product works and might develop a sense of foresight when it comes to pre-empting constraints or issues that may be raised when handing over a project to engineering.

9. Speak to Users

The saying goes that if Henry Ford had asked consumers what they wanted Ford to build, they would have said “Faster Horses”. There are varying viewpoints on when and when not to listen to consumers. The ‘True’ luxury companies, for example, are thought to be the arbiters of taste. They don’t create for the consumer, they simply create— and the consumer follows. Brands in the ‘Premium’ category are the ones who create for the consumer. Unlike luxury products, which are non-comparables, premium products are often compared against peers along the value-to-utility scale— “Am I getting my money’s worth?”.

I don’t have experience with the luxury space personally, but if your product is being built for a consumer (whether B2C or B2B) it’s useful to keep a finger on the pulse of what your users want— whether that’s functionality you are missing or pain points with existing features. Engage with their online communities, set up calls, and create networks of highly engaged users to tap for feedback.

If you are involved with a product, you must speak with users.

It’s not always the case that product teams have the most direct contact with users. In some cases, the sales team have the closest proximity to enterprise customers. Something I have found to be invaluable is an open communication line with sales. The customers they communicate with frequently share valuable feedback on features that will get them over the line for signing a deal. If this information is lost in the siloed environment of the sales team, there will be no sense of urgency or understanding from a product perspective. The feedback should find its way back to the product teams.

Thanks for reading,

Conor

4

A list of bad behaviours that may be signs of old-timer syndrome, from Elad Gil’s High Growth Handbook.

To give one example, if you were looking for North American and European companies1 that have repurchased more than 30% of their sharecount over the last decade, sorted from largest reduction to lowest, you’d have to scroll down to row 23 to find the first non-North American entrant. That would be the UK transport operator, FirstGroup Plc. North America would then dominate again until the next European entrant, in row 80. There is a myriad of factors at play here— including but not limited to differences in regulation, tax efficiency, culture, market structure, and appetite for leverage. Europe has commonly favoured dividend distributions in recent history.

Below is a list of twenty serial share cannibals from the last decade. Most have been consistent buyers over the decade, but I sprinkled in a few alternatives to highlight companies that have more recently picked up their repurchases. Combined, this cherry-picked—confirmation bias cesspit—basket of companies has generated an impressive 23.5% CAGR over the last ten years. Is this useful information? Absolutely not, but it makes for a pretty chart.

There is no science behind the selection. I was primarily interested in exhibiting companies from various industries and countries, to acknowledge that share cannibals can exist in any market.

1) Dillard’s (DDS:NYSE)

• What it does: A department store chain offering apparel, cosmetics, home furnishings, and accessories through its network of retail locations and e-commerce platform. The company generates revenue through direct sales, private-label credit card partnerships, and real estate investments.

• Market cap: $7.8 billion

• Distance from ATH: -2.0%

• Shares repurchased (%, 10Y): 61.4%

• Shares repurchased ($, 10Y): $2.71 billion

• Total return (10Y): +424% (18.0% CAGR)

2) eBay (EBAY:NASDAQ)

• What it does: An online marketplace that connects buyers and sellers to facilitate the sale of new and used goods across various categories, including electronics, fashion, collectables, and more. The company generates revenue primarily through transaction fees, advertising, and payment processing services.

• Market cap: $33.5 billion

• Distance from ATH: -13.9%

• Shares repurchased (%, 10Y): 61.44%

• Shares repurchased ($, 10Y): $36.45 billion

• Total return (10Y): +225% (12.5% CAGR)

3) O'Reilly Automotive (ORLY:NASDAQ)

• What it does: Retailer and distributor of automotive parts, tools, supplies, equipment, and accessories, serving both professional repair shops and do-it-yourself customers. The company generates revenue by selling auto parts and related products through its network of stores and an online platform.

• Market cap: $75.8 billion

• Distance from ATH: -2.3%

• Shares repurchased (%, 10Y): 43.4%

• Shares repurchased ($, 10Y): $21.03 billion

• Total return (10Y): +542% (20.4% CAGR)

  

4) Fair Isaac Corporation (FICO:NYSE)

• What it does: Commonly known as FICO, provides analytics and decision-making software focused on credit scoring, risk management, and fraud detection for financial institutions, businesses, and governments. The company generates revenue through software sales, cloud-based analytics solutions, and licensing fees for its widely used FICO credit score.

• Market cap: $44 billion

• Distance from ATH: -25.1%

• Shares repurchased (%, 10Y): 22.3%

• Shares repurchased ($, 10Y): $5.40 billion

• Total return (10Y): +2,098% (36.2% CAGR)

5) MSCI (MSCI:NYSE)

• What it does: A global provider of investment decision support tools, including indexes, analytics, and ESG (Environmental, Social, and Governance) research, serving asset managers, banks, and hedge funds. The company generates revenue through index licensing fees, subscription-based analytics services, and ESG and climate data solutions.

• Market cap: $44 billion

• Distance from ATH: -15.8%

• Shares repurchased (%, 10Y): 30.7%

• Shares repurchased ($, 10Y): $6.63 billion

• Total return (10Y): +1,020% (27.3% CAGR)

6) Crocs (CROX:NASDAQ)

• What it does: A global footwear company known for its casual, comfortable, and foam-based shoes, including its signature clogs. The company generates revenue through direct-to-consumer sales via its website and retail stores, as well as wholesale distribution to third-party retailers worldwide.

• Market cap: $6.1 billion

• Distance from ATH: -41.0%

• Shares repurchased (%, 10Y): 32.1%

• Shares repurchased ($, 10Y): $2.30 billion

• Total return (10Y): +921% (26.1% CAGR)

7) Williams-Sonoma (WSM:NYSE)

• What it does: A speciality retailer of high-end home goods, including kitchenware, furniture, and décor, operating through brands like Pottery Barn, West Elm, and its namesake Williams-Sonoma. The company generates revenue through direct-to-consumer sales via its e-commerce platform and retail stores, as well as through membership and design consulting services.

• Market cap: $26.4 billion

• Distance from ATH: -2.4%

• Shares repurchased (%, 10Y): 33.2%

• Shares repurchased ($, 10Y): $4.45 billion

• Total return (10Y): +566% (20.9% CAGR)

8) Pandora A/S (PNDORA:CPSE)

• What it does: A Danish jewellery manufacturer and retailer known for its customizable charm bracelets, rings, necklaces, and earrings. The company generates revenue through direct-to-consumer sales via its global network of branded stores and e-commerce platform, as well as wholesale distribution to third-party retailers.

• Market cap: €13.2 billion

• Distance from ATH: -2.4%

• Shares repurchased (%, 10Y): 10.9%

• Shares repurchased ($, 10Y): €4.27 billion

• Total return (10Y): +275% (14.1% CAGR)

9) American Express (AXP:NYSE)

• What it does: A global financial services company specializing in credit cards, payment processing, and travel-related services for consumers and businesses. The company generates revenue through transaction fees charged to merchants, interest on cardholder balances, annual membership fees, and travel and financial services.

• Market cap: $219 billion

• Distance from ATH: -4.7%

• Shares repurchased (%, 10Y): 31.3%

• Shares repurchased ($, 10Y): $41.6 billion

• Total return (10Y): +361% (16.5% CAGR)

10) Dollarama (DOL:TSX)

• What it does: A Canadian discount retailer offering a wide range of low-cost consumer goods, including household essentials, food, and seasonal items. The company generates revenue through direct in-store sales across its extensive retail network and growing e-commerce operations.

• Market cap: C$38.7 billion

• Distance from ATH: -8.8%

• Shares repurchased (%, 10Y): 29.1%

• Shares repurchased ($, 10Y): C$6.12 billion

• Total return (10Y): +617% (21.8% CAGR)

11) Ryanair Holdings (RYA:ISE)

• What it does: A low-cost airline operating across Europe, known for its budget-friendly fares and high-flight frequency. The company generates revenue through ticket sales, ancillary services like baggage fees and seat selection, onboard sales, and partnerships with third-party service providers, including hotels and car rentals.

• Market cap: €21.6 billion

• Distance from ATH: -8.8%

• Shares repurchased (%, 10Y): 20.4%

• Shares repurchased ($, 10Y): €4.92 billion

• Total return (10Y): +114.1% (7.9% CAGR)

12) Next plc (NXT:LSE)

• What it does: UK-based retailer specializing in clothing, footwear, and home products, operating through physical stores, online platforms, and third-party brand partnerships. The company generates revenue from direct sales, online orders, and a consumer credit business that offers financing options to customers.

• Market cap: £11.6 billion

• Distance from ATH: -9.9%

• Shares repurchased (%, 10Y): 20.4%

• Shares repurchased ($, 10Y): £2.61 billion

• Total return (10Y): +95% (6.9% CAGR)

  

13) Booking Holdings (BKNG:NASDAQ)

• What it does: An online travel company that operates platforms like Booking.com, Priceline, Agoda, and Kayak, allowing users to book hotels, flights, rental cars, and vacation packages. The company generates revenue through commission fees on bookings, advertising, and payment processing services.

• Market cap: $167 billion

• Distance from ATH: -5.5%

• Shares repurchased (%, 10Y): 36.8%

• Shares repurchased ($, 10Y): $43.83 billion

• Total return (10Y): +361% (16.5% CAGR)

14) Autozone (AZO:NYSE)

• What it does: A leading retailer and distributor of automotive replacement parts, accessories, and maintenance products, serving both professional mechanics and do-it-yourself customers. The company generates revenue through direct sales at its retail stores and online platform, as well as from commercial delivery services to repair shops.

• Market cap: $58 billion

• Distance from ATH: -0.7%

• Shares repurchased (%, 10Y): 47.4%

• Shares repurchased ($, 10Y): $23.14 billion

• Total return (10Y): +459% (18.8% CAGR)

15) Rightmove plc (RMV:LSE)

• What it does: The UK’s largest online property portal, connecting homebuyers, renters, and sellers with estate agents, letting agents, and new home developers. The company generates revenue primarily through subscription fees and advertising services paid by property professionals to list properties on its platform.

• Market cap: £5.3 billion

• Distance from ATH: -17.0%

• Shares repurchased (%, 10Y): 18.8%

• Shares repurchased ($, 10Y): £995 million

• Total return (10Y): +192% (11.3% CAGR)

  

16) Domino’s Pizza (DPZ:NASDAQ)

• What it does: A global quick-service restaurant chain specializing in pizza delivery and carryout services, operating through company-owned and franchised locations. The company generates revenue through franchise royalties, sales from company-owned stores, and supply chain operations, including selling ingredients and equipment to franchisees.

• Market cap: $16.5 billion

• Distance from ATH: -16.0%

• Shares repurchased (%, 10Y): 37.9%

• Shares repurchased ($, 10Y): $5.87 billion

• Total return (10Y): +430% (18.1% CAGR)

17) Apple (AAPL:NASDAQ)

• What it does: A global technology company that designs, manufactures, and sells consumer electronics, software, and digital services, including the iPhone, Mac, iPad, and Apple Watch. The company generates revenue through hardware sales, subscription services like iCloud and Apple Music, App Store commissions, and licensing fees.

• Market cap: $3.67 trillion

• Distance from ATH: -6.0%

• Shares repurchased (%, 10Y): 35.5%

• Shares repurchased ($, 10Y): $716.3 billion

• Total return (10Y): +762% (24.0% CAGR)

18) Restoration Hardware (RH:NYSE)

• What it does: RH, formerly known as Restoration Hardware, is a luxury home furnishings retailer offering high-end furniture, décor, and design services through its showrooms, catalogues, and online platform. The company generates revenue through direct-to-consumer sales, membership subscriptions, and interior design consulting services.

• Market cap: $7.1 billion

• Distance from ATH: -48.7%

• Shares repurchased (%, 10Y): 53.0%

• Shares repurchased ($, 10Y): $3.82 billion

• Total return (10Y): +341% (16.0% CAGR)

19) Plus500 (PLUS:LSE)

• What it does: A fintech company that provides an online trading platform for retail investors to trade contracts for difference (CFDs) on stocks, forex, commodities, and cryptocurrencies. The company generates revenue primarily through trading spreads, overnight fees, and inactivity fees from its users.

• Market cap: £2.1 billion

• Distance from ATH: -3.1%

• Shares repurchased (%, 10Y): 35.9%

• Shares repurchased ($, 10Y): £560.74 million

• Total return (10Y): +1,175% (29.0% CAGR)

20) Assured Guaranty (AGO:NYSE)

• What it does: A financial services company that provides bond insurance and credit enhancement solutions for municipal, infrastructure, and structured finance markets. The company generates revenue through insurance premiums, investment income from its portfolio, and fees for risk management services.

• Market cap: $4.6 billion

• Distance from ATH: -6.2%

• Shares repurchased (%, 10Y): 68.6%

• Shares repurchased ($, 10Y): $4.48 billion

• Total return (10Y): +309% (15.1% CAGR)

Summary of Stocks Highlighted

Thanks for reading,

Conor

“There is virtue in work and there is virtue in rest. Use both and overlook neither”.

- Alan Cohen

Most investors rely on the stock market to guide their decision-making

The investment industry is structured for activity— like a cacophony of overwhelming sensory cues streamed directly into your eyes, ears, and whatever orifice will accept them. The media encourages short-term thinking, reinforced by artificial constructs like calendar-year performance, quarterly earnings, and price targets. There is permanence in the questioning of why stocks move from day to day and ‘I don’t know’ is never a suitable answer— there always has to be a reason.

To feel comfortable doing nothing, when everyone else appears to be doing something, is to swim against the current. Doing less is a constant cognitive battle and most people fall victim to the market’s siren call at some point.

“Waiting helps you as an investor and a lot of people just can’t stand to wait. If you didn’t get the deferred gratification gene, you’ve got to work very hard to overcome that.” - Charlie Munger

Suppose we can glide between dimensions for a moment. Company A reports a mediocre earnings report— in line with expectations, nothing better, nothing worse. In the first dimension, the stock falls 15% the next day. In the second dimension, it finished the day up 5%. This experiment would not exist in a vacuum. Expectations - one of the myriad factors that can influence post-earnings reactions - will play a large part here. But on the whole, assuming all else equal, the investor is more likely to attribute a negative opinion of the report in dimension one (-15%) and a positive opinion of dimension two (+5%).

Why is this?

This thought experiment illustrates a fundamental truth— most investors use the stock market as a barometer to validate their opinions and decision-making.

A child sitting an exam may feel unconfident about their answer to question 17. Leaning over at their peer’s papers, they glimpse at what they wrote for question 17. Alas, it’s the same answer. Instantly they feel reassured and more confident— unbeknownst to the fact they both provided the wrong answer.

In the worst of outcomes, an investor will glimpse at a post-earnings price reaction before establishing their viewpoint— therefore tainting their perception and reinforcing a framing effect. That is to say, the report will now be consumed with an innate bias and the reader will subconsciously seek out confirmatory information.

In a marginally better outcome, an investor will glimpse at a post-earnings price reaction ex-post— seeking validation on how they perceived the report vs. how the market did— often affording the market’s reaction too great an importance.

There is merit to keeping a pulse on the market’s viewpoint, however. The impact of having a contrary opinion, and putting capital behind it, can be significant in the short to medium term. One need only look at the explosive turnarounds in previously beaten-down large caps like Netflix and Meta Platforms as corroborating evidence. It goes both ways too. Every bubble must come to an end and for a small number of investors who get the timing right, they capitalize on going against the crowd.

However, as the time horizon grows this can exhibit diminishing importance.

While timing is not everything, it still matters

In the summer of 2015, you could have looked at Greggs Plc— a company the market clearly favoured, having risen 290% (14.6% CAGR) over the prior decade. Since the summer of 2013, the stock had gone nowhere but up. Sure, it was a little expensive at the time, but it wouldn’t have been contrarian to own Greggs. If you’d bought at the peak in 2015, it would have taken two years to break even (evidence of being paid to have a contrary short-term outlook). If you’d held on, you would have enjoyed a 10.8% CAGR until the end of 2024.

That CAGR would be chopped down to 7.4% at today’s share price after some negative reactions to management’s commentary on the UK’s 2025 economic outlook at the beginning of the year.

Earlier I mentioned that “as the time horizon grows [timing becomes less important]”. I generally believe that to be true— with caveats. Being long consensus longs is fine, but it is the entry point that will have the most profound influence on long-term return. This is where having a shorter-term perspective can be critical. In the two years following Greggs’ 2015 peak, the forward earnings multiple tumbled from 25x to 15x. If you had waited until the market fell out of love with Greggs and still believed in the long-run opportunity, your return would be closer to a 13.4% CAGR today—or 17.7% by the end of 2024. This underscores that even if you are investing for the long term, the entry price matters. To increase the chance of a favourable entry price, you must engage in short to medium-term thinking. Buying at any price is generally a flawed philosophy— patience to wait for better entry points is typically awarded.

The point I am trying to make is that timing only becomes ‘less’ important, not unimportant.

There is a spectrum. At one extreme there is the ethos of ‘buy only when it trades like it’s going bankrupt’. At the other extreme ‘buy quality at any price’. I believe that the former is arguably more prudent, but requires an incredible amount of patience and likely results in a great deal of lost opportunities— great businesses seldom trade in such a way and it can be enough to acquire fantastic businesses at good or fair prices. The latter can work out but in my opinion, it’s a bolder testament to the fact you are complacent with playing the odds (that are seldom in your favour)— many people like to cite tremendous outliers, the one in 10,000 stocks, as evidence to the contrary but that mentality, for most unfortunate souls, is a recipe for disaster.

You can do very well existing somewhere in the middle of that spectrum— buying quality businesses at fair prices with a long-term horizon and a disciplined process. For the sake of longevity, this approach ought to be beneficial for the common investor. That said, there is no single way to invest, as evidence suggests people can make it work with whatever process is most compatible with their temperament.

I digress.

An investor looking at the market reaction to an earnings report commonly does this as a validation process— “I think X and the market thinks Y, so I am wrong”. While short-term price reactions are useful in some contexts, they are not indicative of truth. After all, it can be tremendously profitable to have a differing opinion from the market and have that opinion justified over the long term. But you have to be right. You can’t expect to be blessed through a strict adherence to patience alone.

This tendency to seek validation from market reactions reflects a deeper human inclination for fairness and reassurance. Whether we know it or not, we seek that reciprocal behaviour in the stock market. As Shakespeare once said, “The quality of mercy is not strained. Upon the place beneath. It is twice blest: It blesseth him that gives and him that takes”.

The pseudo-relationship between market and man is different. The stock market does not show mercy, nor does it benefit from showing it. Unlike in human interactions where mercy can be mutually beneficial, the market is void of compassion. It neither offers leniency nor rewards it.

Why are we bad at selling?

In 2024 I set myself a personal goal to be less active— further insulation from talking heads and to reduce transaction frequency. These two things can go hand-in-hand, as discussed in the introduction. Selling can be the result of pressure, but there are various reasons why we tend to be ‘bad’ at selling stocks.

An article1 from Frank Thormann at Schroders in 2022 was aptly titled ‘Why most investors are bad at selling and what they can do about it’. Referring to the underperformance of active managers, Thormann highlights the damning findings from a 2016 paper by professors Jin and Taffler:

“In a landmark paper, Professors Jin and Taffler (2016) looked at a large sample of over 3000 fund managers over the period spanning from 2003 to 2013. They found that on aggregate buying decisions added 1.4% of outperformance per year, while selling decisions detracted -1.8% annually in underperformance”.

The article describes a handful of biases that work against us humans in the pursuit of selling investments. Thormann surmises that because our brain processes fear and greed differently and the presence of behavioural biases, we are at odds with successful decision-making in this matter.

“Emotion of fear is processed very differently in the brain from the opposite feeling of exuberance because it is processed in a different location. As a result, humans think of (financial) losses very differently to how they think about gains, leading to suboptimal decision-making”.

This question of why we are bad at selling has been studied copiously, such as in Akepanidtaworn2 et al‘s 2018 paper, Selling Fast and Buying Slow, where they conclude that “while investors display skill in buying, their selling decisions underperform substantially—even relative to random-sell strategies”. Also observing institutional investors, this paper used a dataset of 783 portfolios, averaging $573 million in AUM, and covering 4.4 million trades from 2000 to 2016. Employing counterfactual portfolios that used a random selling strategy as a benchmark, they found that genuine selling decisions, made by managers, underperformed by 80 bps annually. Conversely, the genuine buying decisions outperformed the random counterfactual portfolios by 100bps annually.

Both the article and the paper conclude that selling is a neglected skill amongst institutional investors and point to various behavioural biases as a cause. Thormann, the author of the Schroders article, lists commonly understood biases— a summary of which is bulleted below.

1. Loss aversion: “The tendency to allow very recent performance history to shape one’s risk assessment of an investment”.

2. Availability bias: “In complex decision making we do not consider all alternatives equally but quickly jump to the ones which come to mind first”.

3. Confirmation bias: “We have a strong bias to interpret subsequent data points in a way to appear favourable to our original premise”.

The final point he makes is that we tend to spend more time on buying decisions than selling. Just think about it— how long do you spend researching a business before you end up deciding on whether or not you will buy it?

You examine the industry makeup, the market structure, and the business model. You scrutinise potential tailwinds & headwinds, cost structures, unit economics, and the consumer. You dissect the financials, the filings, and the management. You might reach out to peers to hear their take. You should explore confirmatory and contradictory evidence to challenge your base case. You go through numerous stages and burn a considerable amount of time.

Now, think about how long it takes you to decide to sell a stock. If we are being candid, for most it’s not weeks or months— it’s a matter of days. In some cases, hours. Again, there is a spectrum. Act too hastily and you might let an overreaction turn into a mistake. Conversely, sometimes fast reactions can help with calamity avoidance— it’s a good choice to jump out of a nosediving aeroplane while you have a parachute.

The same outcome can be framed in a different light. On the one hand, being methodical and taking time to process information can avoid making an irrational decision of selling pre-emptively. Yet, spend too long pontificating on the details and more damage may be incurred.

I’ve encountered this challenge many times— where the mistake wasn’t exclusively the sale, but the buying decision that preceded it— where the correct buying decision was not to buy and the correct selling decision was to sell 5 seconds after buying. Years ago, I bought into the premise of the PLBY Group squeezing value out of a brand that time had forgotten (Playboy). There was an opportunity for high-margin licensing and company-operated distribution of products and services. Eventually, the red flags compiled and I realized this thesis was not going to play out. I sold my relatively small, speculative, position for ~$6 per share with a 50% haircut. It was the right selling decision in the grand scheme, but it came far too late. The silver lining here was that I was not more hesitant. Within a year or two, the shares fell to $0.50 per share— I had avoided a 96% drawdown. These are relatively inexpensive lessons at my age, and I am grateful to have learned them early.

Investors are rewarded for both action and inaction

It’s natural to circle back to the buying decision when thinking about selling. You might think to yourself ‘If the buying process is perfect you can worry less about the selling’. The reality is that nobody has a 100% hit rate. Every investor will hold a future stinker at some point in their lives— the future is unknowable so what might seem like a strong bet today may require folding tomorrow. But suppose you have divine luck and throughout your life, you manage to exclusively acquire companies that will, at some point, proceed to 100-bag.

At some point, every 100-bagger has a chart that looks like the ones I have shared below (with legends and labels removed for dramatic effect). You are likely to suffer multiple significant drawdowns, years—even decades— of somewhat flat performance, and uncertainty as leaders, consumer tastes, regulation, and business models evolve. In short, regardless of your hit rate, you are going to be challenged with sell decisions. It’s guaranteed.

The market’s short-termism is dictated by sentiment and while timing is not everything, it still matters. I believe that selling is harder than buying, due to the increased influence and quantity of biases. While buying and selling share similar biases (such as FOMO), the introduction of live, unrealised profit and loss, creates a greater sense of urgency and desire to act.

My experience thus far has taught me that purposefully reducing potential triggers to the biases mentioned in this text can go a long way in removing emotion-driven sell decisions, but it won’t absolve them completely.

Errors at the input stage (buying decisions) are like ticking time bombs that, even absent of external stimuli, sit and wait for the self-awareness that you were wrong. The irony is that you can’t know if a buying decision will have a poor ten-year performance on day 1. This is only possible with time.

Investors are rewarded for both action and inaction. The challenge is knowing when to apply each. The desire to tune out of the market hubbub and transact less frequently is not an intent of disengagement— rather, a step towards better decision-making. It’s not about never acting. It’s about acting when it matters most.

Thanks for reading,

Conor

In short, this allows users to upload a time series of data (only requiring dates and units) and that data series will exist as a useable asset within their Koyfin account. The custom data series can be shared, added to Watchlists & Portfolios and can be pulled up in charts. The engine we use to create these custom series also afforded benefits to the rest of the system and other workflows, which I will discuss shortly.

What was the catalyst?

When you release a new feature or workflow, there follows a new timeline of improvements. The first version of a product is never the final one. For example, we launched Model Portfolios in mid-2023. We’ve since launched an abundance of improvements and new features related to that workflow that include but are not limited to, portfolio sleeves, reporting tools, richer exposure exhibits, a holdings matrix to identify exposure overlap, x-ray fund exposure, and more.

The idea for custom data series was born from the fact that Advisors, who use Models, often have clients who own assets that are not publicly traded. By virtue, they are not supported as instruments in Koyfin and can’t be included in their Models or reports. The initial idea was more of a ‘Custom Security’ engine that would allow Advisors to add non-supported or private assets to their portfolios such as corporate or government bonds, private equity, art, annuities, real estate, private funds, and more.

This would have been a great feature nonetheless, but with a few minor tweaks, it could be a great deal more flexible and appeal to an additional segment of consumers.

Custom Security ➝ Custom Data

The term ‘Custom Data Series’ differs in that it’s less definitive. In theory, this engine could be used to create anything, not just tradable securities. Things like company segment data or KPIs, economic data series, or just about anything you’d be interested in tracking on a time series. For example, below is a chart displaying Nielsen data on streaming as a % of US TV time. This data isn’t provided by Koyfin, but it exists publicly, for free, in a time series.

This data set now lives inside of my Koyfin account, I can update it easily and monitor it over time. Similarly, I now input all of the KPIs from the companies in my portfolio to Koyfin and update them quarterly. I can now also add the private equity and options that I own into my portfolio too.

The primary requirement of our first iteration of Custom Data Series was centred around allowing users to create these data sets, supporting them as assets which can be used around the platform, and most importantly enabling them to be added to portfolios. I am confident there are more great improvements we can make to this workflow in the years ahead, and I am equally confident we will gather many great suggestions from users, each of who have different ideas about how this feature can be used. Like other new keystone functions of Koyfin, the first version is never the final one.

Creation

The custom data series live in a user’s ‘My Data’ section, located in their account settings alongside other personal assets like Graph and FA templates or Watchlists. Here, they can be created, edited, managed, shared, deleted, and copied over to a watchlist.

Initial creation requires the series to have a Name, Ticker, Asset Allocation, Instrument Type, and be designated as a monetary (currency) or non-monetary (no currency) item. To upload data, a CSV with Dates and Values is required.

Each item of metadata will serve different purposes throughout the system. Name and Ticker are obvious, these will be used to identify and retrieve the security. These data series will then appear in ticker selection windows for Graphs, Watchlists, Portfolios, and Search.

Instrument Type and Asset Allocation are important as they will now surface in portfolio exposure exhibits. For instance, if you owned a portfolio of 50% SPY and 50% in a private corporate bond fund, the instrument type (corporate bond) and asset allocation (fixed income) would now surface in exposures.

Choosing whether or not a series has a currency is important when distinguishing between tradable assets with a monetary value (e.g. a private hedge fund asset) or a series with a numerical value (e.g. the number of Tesla vehicles sold in 2023).

Appending

Updating the data series can be handled in the My Data section, where users have the choice of uploading a CSV which will overwrite the previous data (+New) or maintain the existing data but add new data on top of it (Append).

Two Functions in One

The engine that we use to create these data series is now being used for other workflows too. Previously, Advisors who connected their custodians via our integration service would be able to pull in clients’ accounts and their positions but were limited by the fact that only securities we have in the system would be ingested.

For instance, if the client owned a Coca-Cola corporate bond, that security would be skipped from the ingestion. Thanks to custom data series, we now automatically ingest these securities, using a mapping from the custodian, and automatically assign their instrument type and asset allocation as well as loading their price, cost, quantity, and P/L data. This means that these securities will now provide a more accurate depiction of the client’s account and populate those allocations in exposure exhibits which then feed through to reporting tools.

I am excited about the custom data series because it feels like we have created something that serves our variety of user personas from Advisors to researchers to data fanatics. I look forward to seeing how users adopt the feature and how we develop this in the coming years.

This functionality is now live for Pro and Advisor Pro users who can create unlimited custom data series. There is also a limit of five custom data series in the Plus plan. If you’d like to test it out (or watch a demo), feel free to reach out to me with your account email and I can set up a trial for you. Equally, if this is the feature you were waiting for the make the jump to Pro, here is a 20% discount code also.

Thanks for reading,

Conor

We are also on the cusp of releasing something huge (with a capital Y). I’d say it’s firmly in my top two for features i’ve worked on in my two years at Koyfin. I’ll write more about that when the time comes, but for now, I wanted to catch up since the last Product Work update I shared back in August.

Below is a variety of the things we have released at Koyfin over the last three months, with some commentary.

1. Advisors

A central theme at Koyfin over the past 18 months has been Advisor workflows. We have incredible word of mouth at Koyfin and are blessed with an abundance of different user personas from the arms of an umbrella of two larger buckets I’ll just refer to as individual researcher types and professionals/teams. Within the professional bucket, we had a strong following among Financial Advisors despite lacking some of the core workflows they needed. We’ve undergone a journey to incorporate more of those workflows into the platform.

Two years ago, Koyfin lacked any portfolio functionality. Today, we have a library of them from My Portfolio for individuals to aggregate their brokerage accounts and track P/L and exposures, Model Portfolios to create custom baskets and proposals, and Client Portfolios to help bring the proposals into the real world with more emphasis on P/L and lot management. On top of that foundation, we have expanded into custodial integration and report generation, and that’s just getting started.

Creating a platform that an individual like me can use at the same time as an Advisor with more nuanced and advanced needs doesn’t come without its dilemmas. We launched an Advisor Pro tier this September to create a clearer distinction between functionality and guidance towards the right plan for a user.

1.1 Client Portfolios

The Model Portfolio functionality began development ~18 months ago and is a core advisor workflow. Advisors use models for all manner of reasons. As far as acquiring clients go, the model acts as the proposed portfolio. These portfolios are based on allocations, and dynamic weightings, and are flexible enough to be used for various purposes. It’s a tool for comparing the client’s current portfolio and fee structure vs. what the Advisor can offer as an alternative.

When the potential client becomes a client, the Client Portfolios function switches focus from simulation to reality. These portfolios are based on the actual structure of the client’s real-world portfolio, with a focus on quantities, lot management, purchase dates, P/L, and total return.

While the UI appears similar to My Portfolio, a feature built for the individual, the Client Portfolios hub allows for multiple portfolios to be created as opposed to a solitary portfolio. Advisors can create, upload, or import, hundreds or thousands of their client portfolios into a central hub and are equipped with the portfolio analytics they need.

Client Portfolios also introduce the concept of a workspace within Koyfin. For teams of Advisors, the Client Portfolios hub can be shared across a multitude of users at once, making portfolio and client management more collaborative.

1.2 Custodial Integration

We introduced our first integration by allowing Advisors to connect to the Schwab Advisor Center to import their client accounts directly from Schwab.

We are early in the integration journey, with greater functionality and a broader range of integrations on our roadmap, but it’s an exciting path to be on which removes friction for Advisors who want to use Koyfin as their primary analytics platform.

1.3 Reports

Report generation tools are a crucial workflow in the acquisition of potential clients and for internal purposes. From our feedback sessions, we understood that Advisors were frustrated at the lack of flexibility in most offerings. They wanted discretion in what gets included in the report and greater customizability.

We took this on board as we developed our first iteration of Koyfin reports, which allow users to generate reports on funds, models, and client portfolios that cover allocations, performance, risk, and portfolio breakdowns. These reports can be used on a single-entity or comparative basis and allow users to add logos, brand colours, and custom text pages for things like investing policy statements or disclosures. The order and inclusion of individual exhibits can be adjusted too.

The initial feedback has been great, and we are already working on the next version of reports to upgrade the functionality further.

1.4 Portfolio Sleeves

If you are not familiar with the concept of Portfolio Sleeves, I suggest watching Christopher Nolan’s Inception; it’s a portfolio within a portfolio.

Sleeves let users combine multiple models into one larger, more complex strategy, helping users build custom asset allocation models by pulling together different components (models), making it easier to tailor investment strategies to their clients’ needs. The underlying holdings of the sleeves will be surfaced in all exposure and report exhibits too.

2. Other Great Stuff

Besides building out Advisor workflows, we have been busy adding functionality that benefits every user. Below are a handful of some of my favourites from the past three months.

2.1 Comparison Graph

At Koyfin we have several core charting functions. The Historical Graph (G) is the Swiss army knife. It does everything and is the most customizable, powerful, and versatile chart tool we have. To make certain charting flows faster and more efficient, we created the Intraday (GIP) and Performance (GM) graphs which are designed to do one job. Intraday proves intraday prices and % changes up to a range of 10 days. The Performance graph provides the total return and CAGR for any security added to the chart. Both are simplified and only contain a menu to add securities instead of a full library of metrics. It gets you from A to B much faster than doing it on a Historical Graph.

The Comparison Graph (GC) is designed as another one of those simplified charting workflows. This chart is designed specifically for comparing metrics across companies and includes features like colour-syncing, auto-syncing of panels, and a different UI for ticker and metric selection. While more efficient than the Historical Graph for this particular workflow, it’s not as flexible concerning merging panels, hiding individual metrics from select tickers, and some of the formatting options for chart styles.

2.2 Quick Actions in Watchlist

Quick Actions are a way to overlay functions on top of a watchlist whereby the watchlist acts as the ‘universe’ on which the function is based. For instance, a customizable feed for filings, news, press releases, and transcripts.

We also added a scatter plot to the Quick Actions menu. In the near term, we have a lot of other functions we could surface here, such as the earnings calendar and the Lots of Charts dashboard. While it’s possible today to use a Watchlist as the universe for these functions, the Quick Actions menu makes this possible without navigating away from the Watchlist section. It also opens the door to creating new, unique, functions such as histograms, bar charts, and more.

2.3 Koyfin Assistant

In beta at the time of writing, we released our first consumer-facing artificial intelligence feature this month, the Koyfin Assistant.

The goal of the Assistant was to assist in support queries rather than being a fully-fledged co-pilot. The knowledge base will help users navigate the platform, inform them how to use features, and provide context on data coverage, functionality, and more. It’s not there to provide stock tips, and it doesn’t currently have access to our data (e.g., asking what Apple’s revenue was in FY22 compared to FY21).

This will be particularly useful for the thousands of new users we onboard to Koyfin each week, most of whom have simple questions the Assistant can handle. While it may appear a small step, it excites me when I consider the other use cases we can develop to improve the platform and reduce the learning hurdle.

2.4 Two-Factor Authentication (2FA)

Following the launch of custodial integrations, and with plans to integrate with more service providers, 2FA was necessary to maintain the level of security throughout the chain. This helps keep you or your client’s sensitive data secure.

Users can now enable 2FA from the profile settings with an authenticator app.

2.5 Fund Percentiles

Koyfin’s percentile ranks are one of the unique datasets we have on the platform. Previously reserved for equities, we created a set of percentiles for US and Canadian ETFs and Mutual Funds.

Users can now see percentiles across performance, characteristics, and quantitative categories. For US ETFs, there are valuation multiples and yield percentiles too. The data is available as a column selection in tables, the screener and the visualized snapshot format.

2.6 3Y and 5Y Equity Percecentiles

In addition to adding fund percentiles, we bolstered our equity percentile offering, adding 3Y and 5Y variants to the existing 10Y and 20Y periods.

This allows for a more holistic, well-rounded, view of an equity’s percentile scores and provides context for both long-term and short-term trends.

2.7 Linear Regression and R2

Linear regression is a statistical method that models the relationship between two variables by fitting a straight line (regression line) through the data points in a scatter chart. It helps to identify trends and predict outcomes while the R² (coefficient of determination) identifies the proportion of variance. In other words, how strong the relationship is.

We added a simple linear regression and R² annotation to our scatter charts which are used throughout the platform on the back of user requests. One improvement we can make here is allowing users to omit outliers from the chart, thus removing them from the equation in tandem.

2.8 Benchmarked Exposures in MYP and CP

The development of the three portfolio features began at different periods. They cater to different needs, so shouldn’t be identical in substance or style, but there were a few gaps in feature parity. Namely, the exposure exhibits of the portfolio.

In My Portfolio (MYP) and Client Portfolios (CP) we introduced richer exposure exhibits (that Model Portfolios (MP) already had) that came with several great upgrades:

• X-ray exposure for funds: We now look underneath ETFs and Mutual Funds to provide exposure breakdowns of the underlying holdings. For instance, a portfolio comprised of 100% S&P 500 ETF represents the exposure of those 500 or so companies.

• Benchmarked exposure: Users can toggle between showing exposures at the portfolio level (via pie charts) or vs. a chosen benchmark (via bar charts).

• 11 new exhibits: From 5 to 16 unique exhibits, we broadened the type of exposure analysis users can conduct on their portfolios.

• Interactive holdings table: Previous exposure pages were aggregated to the top level. For instance, in a sectoral exposure table, we would show you the weight (%) of each sector in the table. Now we break down the underlying holdings of each category and allow users to filter by subcategory (e.g., by consumer discretionary)

2.9 Crypto Support in Portfolios

Plain and simple, we added support for cryptocurrencies in portfolio features.

2.10 Enhanced Currency Support in Portfolios

Across the portfolio features, the portfolio currency is important because all positions, P/L, and returns are converted back to that currency. We increased the number of supported currencies from 11 ➝ 90 to ensure that everyone can make use of the features.

While the bulk of our users reside in either the United States, Canada, or Europe, we have users from across the world and this would have been a welcome update.

I hope to be back discussing another huge product update shortly but until then.

Thanks for reading,

Conor

Following the Q4 earnings in November 2024, an announcement to raise (at $85 per share) a further $64.6 million in proceeds surfaced; once again for CapEx and operating costs. Armed with more than $100 million in cash on the balance sheet (an all-time high) the business is secure for the next few years.

In the fiscal 2024 year, Kura opened 14 new units steering CapEx to $44.3 million, up 65% from the $22.8 million in 2022. A further 14 stores are expected in the fiscal 2025 year, meaning we can expect that figure to approach the $50 million mark with the added maintenance costs of an evergrowing portfolio1 (now 69 stores across 21 States).

Share issuance carries dirty connotations. Kura, whose sharecount has expanded by 43% since 2020, has not shied away from using public markets to acquire growth capital. The cons of doing so are well-known. It’s not sustainable to rely on public favour, it dilutes shareholders, and it can be a wasteful endeavour without capital discipline. It’s my opinion that Kura bucks the trend.

Management has demonstrated savvy capital allocation with respect to share issuance, tapping into the market at times when the share price is scorching hot. They have, at times, favoured this method to avoid or pay down debt appropriately. The signal that Kura has often provided for issuing stock is that of expansion opportunity. Given that growth has outpaced dilution, I believe this has proved to be justified. The added liquidity this affords has resulted in a steady increase in institutional ownership too.

On a per-share basis over the period the sharecount has climbed 43%, revenue (+90%), gross profit (+152%), and book value (+97%) have all more than offset the dilution effect.

A return to pre-pandemic profitability has eluded the business thus far. The last time Kura Sushi reported a positive net income was back in 2019, at a razor-thin margin. Operationally, excluding the insignificant $332,000 in EBIT reported in 2023, they have by all accounts evaded operational profitability since 2019 too. Since then, however, the acceleration in overheads from a considerably more aggressive expansion has been immense. It’s not exactly a moment in the company’s history when they ought to be prioritising profitability over scale. Since 2019, Kura’s revenues have grown 270% at a 30% CAGR, now amounting to $238 million on a trailing basis (up 27% YoY). Management is guiding for revenue growth in the mid-teens for fiscal year 2025.

Signs the economic model is growing stronger over time continue to stack up. While food and labour costs climbed slightly year-over-year on the back of inflation, Kura management maintained a restaurant-level operating margin above 20% for the third consecutive year. The SG&A margin, 14.1% in fiscal 2024, has continued to improve in alignment with CFO, Jeff Utz’s, guidance and is expected to fall another 60bps by fiscal 2025. Average Unit Volumes, up 35% since 2019, held steady at $4.23 million in 2024.

Strength in AUV was no doubt aided by pricing, but this was impressive as Kura’s mid-year was troubled with a decline in traffic. In his post-mortem, CEO Hajime Uba claimed that while initially believing the slowdown was a result of the “sticker shock” (higher pricing) after the implementation of the AB 12282 , his thinking changed to a “wider national macro factor, which has been corroborated by the earnings calls of [industry] peers”.

Comparable restaurant sales growth, which has been in free fall since the middle of 2023, has been in sequential decline since mid-2023. After flirting with a negative comp in Q3, comparable sales dipped into the negative (3.1%) in Q4.

The tide may be changing, however. Uba would remark in the Q4 call that “The sales pressures beginning in April improved significantly over the course of the quarter” which assisted in the company avoiding negative comparable sales for the fiscal year, coming in at 0.7%. This was followed by assurances that the team expect positive comparable sales in the coming fiscal 2025 year.

There isn’t much value in getting distracted by short-term traffic trends; particularly when similar headwinds have been felt across multiple industries. Kura’s guidance is modest and around half of the 2Y average revenue growth rate. It was nice to see a more conservative approach to guidance after the faux pas3 in fiscal 2024. When asked about why the guide is so muted, it seems management wanted to avoid being the cat that touched the stove top twice.

“We're very pleased with the performance that we've seen to date as we've entered the fiscal year September and October. Q1 is definitely outperforming Q4, and we're very happy to see that. But -- it's also true that we're still in mid-process in terms of recovery. And so we feel it's prudent not to be overly aggressive with our revenue guidance at the beginning of the year. The last thing we want to do is to have to do a repeat of downward revenue guidance that we did last year. And so we felt that this was the most prudent approach”.

Five stores have been opened so far in fiscal 2025 with another 6 under construction. There could be some upward revision there given that 35% of the guidance has been delivered before Q1 is over. The expected implementation of the self-seating system is not currently included in the guidance, a variable that management suggests could provide up to 50bps of savings on the labour line item and flow directly to the bottom line as “gravy” to the current guidance. Moreover, as we have seen in the past Kura typically likes to lowball annual guides and provide incremental upgrades with improved clarity. Granted this bit them in the ass in 2024, but there remain a lot of positive opportunities for surprises in the coming year, assuming the macro environment remains stable.

The handful of KPIs worth following for this business remains on track as far as I am concerned, leaving me comfortable with holding for the foreseeable future. One concluding remark I will make is that was I slightly jaded in the summer when the stock sunk to ~$50 per share. In my infinite wisdom, I held off buying this drawdown partly because the position size was comfortable and because I had reservations that the drawdown came at a time of weakness compared to the past few times which came after incredible earnings. I did suggest my significant other take a small position around this time and her investment is now up more than 100%, so not all was lost.

Thanks for reading,

Conor

1

Kura Sushi store distribution by State. In the fiscal fourth quarter, they opened one new store in New York. Subsequent to the quarter they opened five stores; two new states in Oregon and Maryland, one in New Jersey, one in Washington and one in California.

3

An excerpt from my comments in Q3: “At the end of Kura’s fiscal 2023, the company communicated guidance of $241 million (mid-point) in fiscal 2024 revenue. Following successive upgrades in Q1 and Q2, the guide increased to $245 million. The Q3 revision which calls for $236 million is now 2.1% lower than what they guided for in Q4 of last year and implies a 3.7% downgrade from last quarter’s mid-point estimate”.

Ask most rational index investors what annualized return they would be content with over a multi-decade period and many will modestly claim that they’d be content with being on par with the index, so give or take around 8% to 12% (the current 30-year CAGR of the SPY is 11%).

Ask most rational stock-picking investors what annualized return they would be content with over a multi-decade period and most should claim that they’d be content with beating the index. I mean, that’s what all the hard work is for, right? This year it hasn’t been as easy as throwing a dart at the wall to beat the S&P 500, but currently, you’d have had a 39% chance2 of doing so with a single stock at the beginning of 2024.

One stock is fine, but create a basket of, say, ten or twenty stocks and that probability declines dramatically. In years when the indices are performing so well, or particular sectors or industries, it can be tempting to look around you and be envious. Other investors will share triple-digit YTD returns and make you feel that your returns, which in any other circumstance may be considered great for a calendar year, feel paltry. I’d bet this comes with no thought to the differing style, concentration, risk appetite, and so on.

An 8% annual return is nothing to be scoffed at. Do this over 30 years and your initial investment will have grown by a multiple of 10 times. Forget the market and what others are doing for a moment. The fact is that the average human being is not earning anywhere close to an 8% return on their savings over such a long period. The average human doesn’t invest, doesn’t understand the power of compounding, nor do they have the mindset that facilitates being upset about an 8% annual return. If you frequent the social sphere of investing, you must remind yourself that it exists in a bubble - a vacuum.

No investor’s journey, or return profile, looks the same. We constantly overestimate how well others are doing. It’s a flaw in our perceptive abilities that has been accentuated through the advent of the internet. Some are willing to take on greater volatility to earn outsized returns. These people ought to be compensated for their risk, but equally suffer the consequences.

Below is a chart that shows three unique return series indexed from 100 over 30 years. They share an identical CAGR of 8%.

The white line (steady returns) earns a consistent 8% per year. The blue line (low returns with spike) earns a sub-par annual return, culminating in an incredible final year. The red line (volatile returns) has a high variance in annual returns with incredible peaks and gut-clenching drawdowns. These are naturally the extremes of what a typical return profile looks like but are illustrative of why a single year of performance is nothing to get worked up about or place too much emphasis on.

There is merit in the adage that you shouldn’t confuse investing your life savings with a hobby. As an avenue to channel your passions and something which is generally thought of as fun, investing can feel like a hobby during the good times. You wake up, your stocks are up, and your returns are great. One of your companies reports mediocre earnings, the market rewards it with a 5% intraday gain. You are winning, your friends are winning, and the media laps up coverage of investors who are enjoying an anomaly of single-year performance with unorthodox investing styles. Maybe a few “[insert name] is the new Buffett” articles surface.

It doesn’t feel like much of a hobby when this trend reverses. This is why we see such high exit rates from stock picking by individual investors during the downturn. Some of them scolded beyond repair, may never return as their bull market brains are left melting on the sidewalk.

I am a strong advocate of the notion that part of the joy of picking stocks is the challenge and the personal development that comes with it. You learn new skills, meet new people, learn more about the world, learn more about the psychological underpinnings of human behaviour, and learn more about your own mentality. Ardent adversaries of this idea will say that you are kidding yourself. That it’s not worth sacrificing the time and effort if you are not going to beat the index. I think there is no right answer here, but if there was it probably lies somewhere in between both certitudes. In the long run, we are all dead. Life is too short to criticize how others spend their time or rationalize their investment decisions.

I’ll conclude by sharing a passage from Howard Marks which seemed appropriate. Abdullah, the author of Mostly Borrowed Ideas, shared this passage with the apt expression “The person up 100% will not come back next year to tell you they are down 50%”.

“As the memo says, back in 1990, I had two interesting experiences, in short order. A certain value investment firm had a really terrible year. They were heavy in the banks, which were deep value, and the banks did terribly. And so, the head of the firm comes out and he says, “Well, if you want to be in the top 5% of money managers, you have to be willing to be in the bottom 5%.” My reaction was, “I don’t care if I’m in the top 5% in any given individual year, and my clients certainly are not willing to have me be in the bottom 5%, and neither am I.

Well, around the same time, I had dinner with one of my clients, Dave VanBenschoten, who ran the pension fund at General Mills. And he told me that he’d been doing it for 14 years, and in the 14 years, the General Mills equities had never been above the 27th percentile of the pension universe or below the 47th percentile. So, 27th to 47th, solidly in the second quartile every year for 14 years in a row. Where did that place them for the whole 14 years? Were they in the 27th or the 47th or maybe average it and maybe the 37th? No, they were in the 4th percentile. So how can a firm that’s never been out of the second quartile be up in the 4th percentile for the whole period? And the answer is, most people eventually shoot themselves in the foot. And, one or more terrible years can ruin a record for the long term”.

- Howard Marks

In the past, Marks has likened retail investing to amateur tennis. Like tennis, people can be successful investors by playing their own version of the game. What makes investing unique is that the court is shared by everyone at the same time. Regardless of which game you play, you are still competing with the professionals, whether you realise it or not. This echoes the writings of Charles Ellis from the 1970s. In 1975, Ellis wrote that “tennis was not one game but two. One game of tennis is played by professionals and a very few gifted amateurs; the other is played by all the rest of us”. He suggests the former play a “winner’s game” where the outcome is decided by the skill of the players while the latter play the “loser’s game” where the outcome is decided by how many unforced errors each player makes.

“Pros win serves, hit aces and score points after long, exciting rallies; successful amateurs on the other hand simply return the ball to their opponent until they almost inevitably make an unforced error.”

- Charles Ellis

There will always be someone doing better than you, getting rich faster, and finding more success. Investing success should be measured in decades and more success would come from taking the time to mind your own business and focus on what lessons you should not be learning as you develop your skillset.

Thanks for reading,

Conor

1

YTD Total Returns of the SPY, ACWI, VTI, and QQQ ETFs, as of November 25th market close.

A few weeks ago I read a piece by Joe Wiggins that asked why investors play low-probability games. He said, “Being an investor is like walking into a casino and seeing everyone crowded around a table playing the game with the worst odds of success”. The odds of “positive outcomes are poor, yet we carry on regardless”, he continues. There is some subtext to unpack here of course. What is a ‘positive outcome’ to you might look different to me. For some, it’s an ambiguous desire to beat inflation, earn more than a checking account interest rate, or compound wealth over time. For others, it’s a desire to ‘beat the market’ or an equivalent barometer of success.

In the case of the latter, Joe is astutely correct. The odds of an individual earning a surplus return to the S&P 500 over a lifetime are incredibly slim. Yet they attempt it anyway. Wiggins’ essay is concise and proceeds to list several reasons why investors are drawn to low-probability games. I am particularly fond of his concluding remark.

“As investors we spend far too much time focusing on how to win the game we are playing, rather than understanding the reasons we are playing at all”.

- Joe Wiggins, Why Do Investors Play Low Probability Games?

Just as investors persist in chasing improbable gains, our daily decisions are often marked by similar contradictions where small rewards lure us into significant risks. In general, we should avoid putting ourselves in situations with high risk and low reward. The earlier examples have two things in common; the perceived probability of a negative outcome often feels small, negligible even, and the risk-to-reward dynamic is skewed, with the potential risks far outweighing the minimal rewards. We convince ourselves that "it won't happen to me”.

Humans have a penchant for cognitive dissonance. When we hold two contradictory beliefs or feelings we are motivated to pick a winner; thus eliminating inconsistency and reducing anxiety as we alter our beliefs or actions to complement the desired outcome.

Every smoker knows that smoking is harmful. Every smoker relishes the soothing hit of dopamine that coats their brain’s reward system when they take a drag. The desire to feel that dopamine is so strong that the addiction triumphs; and so continuing to smoke despite being aware of its harm is an example of cognitive dissonance. Emotions are an unfathomably powerful motivator. They are the world’s greatest gaslighter. They are capable of blinding us to reality in pursuit of desire.

Something which is intrinsically linked to emotion is our fundamental belief system; whether born of culture, environment, or personal experience, it shapes how we view the world and often overrides logic. These beliefs tend to encourage cognitive dissonance too. Factors like our tendency to be risk-averse, or our need to feel like we are in control.

Road vs Air

These two foundational human attributes are often in conflict with the world around us. The difference in how safe we feel when flying on commercial aircraft vs. driving down the motorway is a great example. Air travel is the safest form of transport. The rate of incidents per journey is significantly lower than a road-bound vehicle. Yet, it’s common to know someone afraid of flying and rare to know someone unwilling to step foot in a car.

Travel 100,000 miles by car and there is a ~4.8% chance you will be injured to some degree1. The same distance by aircraft is as good as 0%. The World Bank estimates that there are 0.05 fatalities per million aircraft passengers. In other words, about 1 fatality for every 20 million passengers. They also estimate there are 135 fatalities per million passengers for vehicles or about 1 fatality for every 7,407 passengers. Ceteris paribus, you are more likely to be injured in a vehicle than an aircraft.

Vehicular death rates vary globally. Developed nations with better infrastructure and rule of law typically see fewer fatalities. But the point stands, it’s much safer to travel by air. Where we humans get hung up is that the negative outcome of an incident in the air is near certain death. In a binary fashion, we either survive or face catastrophe. On the other hand, the range of outcomes of an incident in a car is more palatable. This is all to say that we are generally irrational in how we perceive the relationship between risk and reward or probabilities.

DCF: Dillusion of Control Framework

The discounted cash flow model is a means to an end. It can also help us understand how we deceive ourselves in pursuit of the need to be in control. You plug in some inputs and those inputs estimate the fair value of an investment based on its expected future cash flows, adjusted to account for the time value of money. A reverse discounted cash flow model flips the hierarchy so that you start with a current value and work backwards to find the required inputs for said current valuation. In other words, you are measuring the implied expectations and deciding if they are acceptable.

They can be immensely useful, and equally precarious. Investing has a scare factor. It’s uncertain, the future is unknowable, and there is an infinite concoction of variables that can influence the outcome both within and outside the company’s control. The most influential factor is your own decision-making and temperament.

Wouldn’t it be nice if there was a tool that we plug numbers into and tells us if something is a buy or a sell at the current price? Doesn’t that just make life easier? It washes all of the uncertainty away. Investors can subconsciously fall into the trap of forgetting that models are not a get-out-of-uncertainty-free card.

Ben Graham’s concept of ‘intrinsic value’, later popularised by Warren Buffett, is flawed in that it’s entirely conjectural. Both intrinsic value and fair value are theoretical constructs, meaning they aren’t “real” in the sense that they’re not fixed or universally agreed upon. Instead, they represent estimates of what an asset is truly worth, based on different models, assumptions, and perspectives. In short, while the methodology used to derive an output is quantitative, the output itself is then subject to subjectivity. It’s a matter of opinion, and the saying goes that opinions are like arseholes…. everybody has one.

An investor will never be in control of the market. The best they can do is succumb to that reality and find a way to deal with it. Focus on the variables they do have control over. Ensure they have a process which eliminates as much undesired human behaviour as possible. One that nurtures rational thinking and common sense. If you know you are sailing through the waters of Siren, the best thing to do is tie yourself to the mast or cover your ears.

Something as simple as a cash flow model, when relied upon too extensively, can confound the fear of not being in control and create the illusion that we are.

High-Risk Low-Probability

Until now i’ve used the notion of stakes and risk or reward and probability interchangeably, but they are not the same. The terms high stakes, low reward and high risk, low probability are different dimensions of decision-making that have some overlapping matter. The best way I can describe it is through the roulette table.

High Stakes, Low Reward: You play by betting on red or black

• Stakes: You can bet a significant amount of money (high stakes), but the potential reward is minimal (only doubling your bet). The odds of winning are close to 50%.

• Low Reward: Even if you win, the reward is small compared to the amount at risk. You double your money, but the risk (losing your entire bet) is large for what you stand to gain.

High Risk, Low Probability: You play by betting on a single number

• Risk: The risk is still high (you could lose everything you bet), but the reward is significantly higher, at 35 times your bet.

• Low Probability: The reward may be higher, but now the probability of winning is extremely low. Depending on where you are in the world, the probability is 1 in 37 (2.7%) or 1 in 38 (2.63%).

It can be useful to tackle decision-making through both lenses, but I would argue in favour of taking a risk-probability approach. The idea of ‘reward’ flirts with subjectivity while ‘probability’ is closer to a universal truth. Whatever game you find yourself contemplating, it’s best to think about what you stand to lose, what you stand to gain, and what the probability of a positive and negative outcome is.

Why Are We Drawn to Low Probability?

Taking one of Wiggins’ examples, he suggests that being “uncommonly skilful” is “the only reason to engage in a game where the odds for the average player are poor”. If a peak Roger Federer participated in a knock-out tennis tournament of 100 players, the basic odds of success (winning the competition) is 1 in 100 (1%) for the average player. For Federer, they would be considerably higher, and so he should play. I don’t know exactly how to calculate that, but it’s undoubtedly true.

The perception of elevated skill, accurate or not, can result in willful ignorance. Through that ignorance, we may be motivated to engage in activities in which the probability of success is considerably lower than what we believe. The problem with investing, in particular, is that everyone thinks they are the 5% when it comes to beating the market. Despite knowing the odds of success are slim, seasoned investors believe they can defy the odds anyway. That’s willful ignorance, but what about plain old ignorance?

The term ‘ignorance is bliss’ means that you don’t know what you don’t know. Your understanding of the game is so limited, that you are deeply unaware of your own ignorance. Much like you shouldn’t scold a child for repeating something a parent has said, it’s hard to criticise the blissfully unaware. Only through experience, can ignorance be chipped away. I believe the trajectory for many investors is they start investing with the desire to beat the market because they don’t know any better. Over time, every rational investor appreciates how difficult this is in reality. They will reach a crossroads, and the paths diverge:

• Willful ignorance: They continue under the belief that they will defy the odds.

• Graceful acceptance: They continue despite the realization that they are unlikely to beat the market. Perhaps they change their goals to be less centred around ‘beating the market’. For many, investing is fun. It’s a way to understand the world while growing wealth over time. Despite what some might say, there is not only one reason to invest.

• Beach mode: They continue to invest, but reallocate into funds or other passive investments. They exit, or significantly reduce, their exposure to individual stocks and settle for ‘market’ returns. They have more time to enjoy their limited time on earth.

Sometimes, the fact we know the odds of success are so low creates an element of excitement. Remember the internet sensation that was the ‘bottle flip’ challenge? You take a water bottle by the neck, flip it, and try to make it land upright. Before realising the ‘trick’ to make it land upright every time, it’s a difficult task. The odds of success are low, but it’s fun so we try it another 20 times. What about carnival games? By this point, I think everyone knows each game at a carnival has an element of rigging to ensure customers seldom win and take home a prize. We know this, we know the odds of success are slim, but that makes it fun and that much more satisfying when we do win. With investing, however, fun is usually not a great sign. If you are passionate about it, it can certainly be enjoyable, but as Wiggins correctly remarks, “The challenge for investors is that it is the boring stuff that works. And nobody wants to play a dull game”.

Social proof is another reason we are drawn to low probability. The idea of herd mentality is well-studied. If a group of our peers do something, then we feel less reservation about doing it too. This creates an environment whereby outcomes are thought of less in terms of “how likely is this” and more in terms of “wow, this is what I can win”. Consider the lottery. The greatest visibility is given to those who overcome the odds and win. You don’t hear anyone say “remember that guy who almost won the lottery?”. If you make it to the Olympics and come 10th in your chosen sport, then you are in the top 10 of that sport in the world. An incredible achievement. Yet, outside of a niche circle of influence, nobody remembers you. To point to a more recent example, recall how aggressively the rise of NFTs entered the social sphere and how quickly and silently it left.

So long as there is evidence of people overcoming the odds, the idea that you can be the next person to do so will persist. The social proof of almost everything has grown exponentially since the birth of global media and social platforms. It’s why young adults are so desperate to live beyond their means. It’s why everyone thinks they can pick a few stocks and beat the market by reading a few books and 10-Ks. In bull markets, the inception phase of buying a stock is considered in terms of “how much money I will make” and less in terms of “what are odds this stock performs well over a given period”.

Ironically, it is usually when the bull market ends, things are less ‘fun’ and fewer people are harping about their YTD returns, that investors go through their most transformative reflection periods. Because you are no longer infatuated and occupied with the pleasure of feeling like a genius, you find yourself contemplating more often. “Where did I go wrong? How can I improve?”. This is true for all vocations in life. All experience is good experience, and hard times create stronger individuals.

Despite sometimes knowing the risks, humans are drawn to high-risk, low-reward activities due to emotional drivers, cognitive dissonance, and the illusion of control. Whether it’s investing, not wearing a seatbelt, or playing a rigged game, the lure of small rewards or perceived mastery keeps us engaged, even when logic suggests we should walk away.

Maintaining a state of mind that is resistant to being pulled towards hyperbole or despair is easier said than done. Thinking of games in terms of risk and probability is a rational person’s endevour, which is a challenge in and of itself. A challenge worthy of pursuit, if you ask me.

Thanks for reading,

Conor

As more knowledge is accumulated, the desire the use that newfound knowledge grows stronger. In an attempt to make use of it all, tasks become burdened with complexity. The path from student to mastery begins with favouring simplicity, then complexity, and concludes with simplicity. The reason students should learn from masters, and not intermediates, is that both place a high value on simplicity.

The character arc of the chef is a great example. A beginner starts out by learning the fundamentals, following recipes, and practising basic techniques. The intermediate expands their horizons, incorporates advanced techniques, and new flavour combinations, and overcomplicates. The master understands food so deeply that they can harness a few high-quality ingredients and techniques to create something seemingly understated in appearance, but incredible in flavour. Marco Pierre White once owned a restaurant that earned the accolade of three Michelin stars. In a move that was unprecedented at the time, he would later hand them back. As he matured in age and skill, he would frequently remark that the desire to return to simple cooking was his motivation.

“Simplicity is the secret to everything”, he would often say. “The more you add, the more you're taking away”. This is part of the reason why Italian food is held in such high acclaim. It focuses on the quality, not the quantity, of ingredients.

There are many great quotes like this. One of my favourites is a line from Coco Chanel, in which she suggests “Before you leave the house, look in the mirror and take one thing off”. The point is that no matter what skill or profession, the end game always appears to circle back to simplicity.

Let’s run through a couple of other examples. We’ve covered my favourite pastime, cooking, so now let’s migrate to my own profession; that of the product manager. A product manager’s role is multi-faceted. At its core it is about two things; understanding what users want and knowing how to translate that demand into a product and communicate the vision to an engineer. These two things are the simplest descriptions of the role and what both new and tenured managers will strive for. Somewhere in between, there is a hodgepodge of advanced user flows, features nobody asked for, unnecessarily complicated UI, analysis paralysis, and product bloat. The temptation to overcomplicate has not yet succumbed to the even greater temptation to strip away unwanted complexity.

Consider the iPhone. It’s a technological wonder. It’s many human’s third arm and second brain. Yet it’s not the most technically advanced phone on the market. It hasn’t been for some time. What it does better than any other product in the market, and dare I say the world, is package up technology which is so incomprehensibly complex to the common individual in a manner that is so sophisticatedly simple.

Lastly let’s consider one of my greater passions in life, investing. Every single investor follows the Good Will Hunting Arc (see below).

You start at a crossroads with a seemingly endless number of paths to explore. Fundamental analysis, technical analysis, value investing, accounting, benchmarking, long-term, short-term, derivatives, discounted cash flows, models, macro, and the list goes on. This tends to be when you are at your most humble. When you pick up a few things you likely go through various phases. Like teenagers going through a goth or chav moment, investors will find themself switching genres often as they try to find the style that suits their temperament. I am sure everyone goes through a small cap phase. Some begin to fetishize macro and illiquid deep-value opportunities. As you pick up new knowledge, you try your best to cram as much of it into your process as possible.

But a fatter checklist doesn’t equate to better returns. Another way to frame it is simply by the transition of learning that it’s incredibly difficult to beat the market, to then feeling confident you can do it over the long term, to ultimately appreciating the difficulty of such an act. I am no beginner, but I am no master either. Over time I have come to appreciate that I’d rather optimise for spending as little time in front of a screen as possible. Do the heavy work up front, keep an active watchlist of opportunities, track the handful of core KPIs that make the business tick for each company, understand the thesis, be prepared to re-allocate if it derails or you feel you were wrong, keep up to date each quarter, and let time do its thing. Stay away from CNBC, avoid placing too much emphasis on macro, and aim to check your returns as infrequently as possible. A richer news diet is more likely to congest your clarity. Like information-cholesterol for the brain.

Beginners and masters share one thing in common; a penchant for simplicity. They are two different forms of desire. The beginners want things to be communicated simply so that they can understand. The master wants that too, but the differences lie in from their ability to take a complex subject matter and communicate it as though it were simple. When you hear someone say “they make it look easy!” it’s because that person has a deep enough level of understanding in their craft to do so.

“Simplicity is the ultimate sophistication. It takes a lot of hard work to make something simple, to truly understand the underlying challenges and come up with elegant solutions. It's not just minimalism or the absence of clutter. It involves digging through the depth of complexity. To be truly simple, you have to go really deep. [You have to deeply understand the essence of a product in order to be able to get rid of the parts that are not essential”. - Steve Jobs

A student asks two mentors a question. The intermediate will respond with an answer that leaves the beginner with more questions. The master will respond in a way that answers the question.

How do I cook a perfect steak? They may ask.

Answer 1: "To cook the perfect steak, start by choosing the right cut, like a ribeye or filet mignon, with marbling. Make sure the steak is at room temperature before cooking. Season it with a mix of kosher salt, black pepper, garlic powder, and a hint of rosemary. Use a cast-iron skillet, and preheat it to exactly 260°C. Sear the steak for exactly 2 minutes on each side, then baste it with a mixture of butter, thyme, and crushed garlic. After that, transfer it to a 190°C oven and use a meat thermometer to ensure the internal temperature reaches 55°C for medium-rare. Let it rest for 5-7 minutes under a foil tent to redistribute the juices. Serve it on a warm plate with a side of homemade chimichurri sauce and garnish with sea salt flakes."

Answer 2: "Season it well, cook it hot and fast, and let it rest before eating."

As for why people tend to gravitate back to simplicity, I think there comes a point when the value gained from time spent learning a particular subject matter begins to diminish.

At the start the rate of growth is incredible. Everything is new. By the time that begins to peak the newness dissipates, complexity fades, and a desire for elegance comes to the fore. The new challenge is taking what you know, and making it seem simple. That is the paradox of the complexity curve.

Thanks for reading,

Conor

This month contains a handful of articles that I enjoyed reading recently. Life has been super busy lately, so my reading diet has been light; focussed on essential transcripts and filings, and a few papers when I find the time. I am heading back to India this weekend, for some much-needed sunshine now that Scotland is transitioning into Autumn.

In each edition of the TLDR you can expect:

• 5x Favourite Things: 5 favourite reads.

• Honourable Mentions: Other worthy reads.

  • Excluded from this edition.

• Uncharted Perspective: 5 favourite charts.

Read more