We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.
Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!
But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.
Here are the articles for the week ending 01 November 2026:
1. Most Improbable Agent of You – Kevin Kelly
AI today is probably the most centralized it will ever be as well. Currently the most reliable way we know how to make AIs smarter is to make them bigger. This principle is called the scaling law…
…That scaling results in massive computer processing centers, running millions of chips, with trillions of parameters, powered by gigawatts of energy, costing tens of billions of dollars…
…On the other hand, each one of us runs a very powerful (better than most AIs), very tiny (big as your skull), very energy efficient supercomputer running only on 25 watts at the end of our necks. There are some 8 billion of these tiny supercomputers spread around the planet, interconnected via the internet. We have an existence proof that biological intelligence does not need to be centralized.
Today, because of rapid innovation in AI architectures and training formulas, the amount of compute an AI needs to deliver a given capability has been cut roughly in half every 8 months. Combine that with the hardware gains of Moore’s Law, and the cost per capability halves roughly every 6–7 months. Assuming Moore’s Law continues, within a few years, a model as capable as today’s leading LLM – let’s call it Opus – could run on a device you own. Within about a decade, the cost of training one from scratch would be affordable by an individual, and fine-tuning your own copy would cost far less.
That means everyone could own and control an AI like today’s Claude or ChatGPT or Gemini. You would not have to ask permission to do things, or be obligated to train it with certain guidelines, nor have to accommodate the preferences and sensitivities of others. The AI could reflect you…
…Many of the issues that people have with AI today would be resolved if the AI were not only available from a huge massive monopolistic tech company, but instead was generated, delivered, overseen, and maintained by individuals. A lot of the criticism of AI today is really just a criticism of capitalism. There is the question of who benefits from the value being created, who controls who gets what (the best AI models may be kept for internal use by some companies), who gets to train the AI mind, and supervise what it is trained on, and who decides what it is used for…
…I want a personal AI that I have trained myself on all my life’s experiences, all the influences I have had, all the work I have done, and all the people I most admire. There will be advice and schools for training your personal AI to become the most useful to you. In fact there will be teacher AIs who educate personal AIs, and people will hold opinions on the best way to educate your personal AI and what kind of AI teachers you want. You want the teachers weird but not too weird. You may want to train your personal AI on the classics, rather than everything. The current frontier models are trained on everything and they are aimed at everyone for all problems. They are by default, generalists hitting the average in the middle of the mainstream.
But we want a personal AI, an exoself, that is as unique as we are. We don’t want the best AI, we want the ONLY AI. We want an AI that is as improbable as we are, and improbable in the same unique direction that we lean. We’ll want to curate the education of our AI.
2. Earnings & Expectations – Ben Carlson
Earnings growth and stock prices were more or less in line with one another in the 1940s, 1960s, 2000s, 2010s and 2020s (thus far).
As bad as the stock market did in the 1930s, earnings were even worse. Earnings far outpaced the stock market in the 1970s. The stock market was up far more than profits in the 1950s. Same thing in the 1980s and 1990s in terms of growth.
These divergences can be even greater in any given year:..
…A wide spread between earnings growth and stock market returns looks to be the norm. The average absolute spread between the two numbers is almost 25%.
This can be even more pronounced in individual securities and sectors…
…Profits for semiconductors are up nearly 200% while the stocks are up a little more than 40% on the year. And they are currently in a drawdown of more than 20% from the highs.
Fundamentals tell the story but you also have to take into account expectations and what’s priced into stocks. Most of the time no one knows what’s priced in.
In the long run fundamentals drive the stock market. In the short run the market and earnings are not always in lockstep with one another.
This is what makes investing in the stock market equal parts exciting and infuriating.
3. 5 myths and misunderstandings about investing in the stock market – Sam Ro
One of the most popular ways to measure value is to divide an asset’s price by its earnings. This is the price-to-earnings (P/E) ratio. When a stock’s P/E is above its historical average, it’s considered expensive. When it’s below average, it’s considered cheap.
This has led many to assume that expensive stocks tend to get cheaper and cheap stocks tend to get more expensive. In other words, valuations tend to revert to a mean, right?
“We cannot emphasize enough that valuation metrics are NOT historically mean-reverting,” Goldman Sachs analysts wrote in January. They’ve characterized it as “an oft-repeated myth.”
The firm has advanced this controversial view since 2013 (and again in 2022 and 2025). To make their point, they used a Dickey-Fuller test, a tool statisticians use to analyze time-series data. The test found that P/E ratios lacked stationarity, which means the averages aren’t stable over time.
This conclusion aligns with arguments from some top Wall Street strategists in recent years. They’ve argued that persistent improvements in business performance and capital structures have justified the higher valuations we’ve seen lately, an idea supported by theory.
And so, the mean itself is moving.
The idea that valuations aren’t mean-reverting probably makes a lot of people uncomfortable. Then again, trading based on the assumption of mean reversion hasn’t exactly yielded consistent results for people…
…Let’s say you got lucky and managed to buy one of these few stocks that go on to smoke the rest of the market. Buckle up.
In a report published last year, Morgan Stanley’s Michael Mauboussin and Dan Callahan studied the price behavior of 6,500 stocks. They took a closer look at the 20 stocks with the best total shareholder returns over the 40 years from 1985 to 2024.
“The median maximum drawdown was 72% for the best group, and the median maximum drawdown duration, the time from peak to trough, was 2.9 years,” they found. “The median time to return to the prior peak was 4.3 years.”
Just thinking about one of my positions losing 72% of its value makes me queasy, even knowing full well this is the average behavior of the best stocks.
4. Why Smart People Make Dumb Decisions – Ben Carlson
A high income, large portfolio, diploma from a prestigious university, or enviable job title doesn’t automatically qualify you to manage money successfully. In fact, many of the worst investors are highly successful in other fields.
In a roundtable discussion following a visit to Theranos in 2015, Vice President Joe Biden stated he had just witnessed, “the laboratory of the future.” Theranos is the Silicon Valley healthcare company that promised it could take a pinprick of blood from a patient’s fingertip to run a series of diagnostics that would revolutionize the blood-testing process. The company was founded by Elizabeth Holmes, who dropped out of Stanford at age 19 to create a device that, according to her, was “the most important thing humanity has ever built.”
The Holmes story was the perfect Silicon Valley fairy tale, destined to become a best-selling business book and movie. Sadly, this fairy tale turned out to be more of a horror flick, for patients and investors alike…
…Her story was so convincing she managed to fool a who’s who of the wealthy elite. The Walton family, heirs to the Walmart fortune, lost $150 million. Media mogul Rupert Murdoch put $125 million into the company based strictly on gut feel alone. He would later sell the entire stake for $1 to take a tax write-off for the enormous loss on a worthless investment. Betsy DeVos, the Education Secretary for President Trump, and her wealthy family lost $100 million. The list of investors also included New England Patriots owner Robert Kraft, Mexican billionaire Carlos Slim, and a Greek shipping magnate…
…Brendan Moynihan tells the story of Jim Paul in his book, What I Learned Losing a Million Dollars. Paul made a killing trading commodities as a young man but lost a fortune once the fianncual windfall went to his head.
Moynihan learned from Paul that, “Personalizing successes sets people up for disastrous failure. They begin to treat the successes totally as a personal reflection of their abilities rather than the result of capitalizing on a good opportunity, being at the right place at the right time, or even being just plain lucky. They think their mere involvement in an undertaking guarantees success.”
Said another way, smarter people may be worse off than others at recognizing their own limitations. This makes sense when you realize intelligent people have more firepower to convince themselves through the power of self deception.
5. Business Momentum versus Price Momentum – Eugene Ng
Traditional value investing teaches that prices matter. It is far better to buy something cheap than expensive. The larger the margin of safety, the better. Low prices (valuations) are far more desirable than high prices (valuations). When prices recover from oversold levels and mean-revert, returns become very attractive.
However, this critically assumes the underlying asset’s fundamentals remain unchanged. While price narratives can inaccurately drive business narratives (especially for commentators) in the short term, business narratives actually drive price narratives over the long term…
…The four losers (Paycom Software, PayPal, Lululemon, and The Trade Desk) we exited share one pattern. When revenue growth structurally decelerates and fails to reaccelerate, past high growth is unlikely to return. It becomes a one-way freight train that is hard to reverse.
The newer, bigger realization is that (business) momentum tends to persist positively or negatively. Momentum seldom reverses, which is why turnarounds seldom turn. That became increasingly evident in these four companies, and when we saw fundamentals keep deteriorating, and growth drift into single digits, we cut our weeds and watered our flowers and new seeds instead…
…Occasionally, Mr. Market provides excellent opportunities for coiled springs, but they are the exception, not the norm. Coiled springs offer the best returns, but they are the rarest and the hardest to verify. There is some risk that Mr. Market knows something and starts to heavily discount the stock before the quarterly financials reflect it, so one needs to tread more cautiously…
…Take The Trade Desk, for example. We thought it was a compounder. Its co-founder and CTO, Dave Pickles, stepped down in September 2023 before we bought, and we underestimated the impact. Internal product development soon slowed, and Kokai’s product rollout struggled. As revenue growth continued to decelerate against still-strong industry growth, it became a value trap we no longer want to own. Follow the business momentum, not price.
Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have no vested interest in any companies mentioned. Holdings are subject to change at any time.