Why Even Smart Investors Lose Money: An Analysis of Mistakes in the Investment Market

Even the most competent people make catastrophic mistakes in the investment market. Why? Because the investment market is steeped in superstitions, rumors, and ideas that have nothing to do with reality.

The blame lies with two factors. The first is the human desire to make money. Where desire is strong, many stories and myths arise. The second is a powerful industry that facilitates investing and has an interest in people believing these myths. When people trade more actively and put money into dubious ventures, everyone earns commissions.

But there is a more fundamental problem: there is no real science or theory of investing. Investment markets are a space of chaos. In mathematics, chaos is not disorder, but a situation in which very small changes in input parameters significantly alter the state of the entire system.

A few words from the president or a commentator can move markets by tens of percentage points. Massive liquidity shifts occur, and many people lose money. It is impossible to predict this.

History shows that even economic geniuses lose money.

Irving Fisher was a great economist; his equation formed the basis of the U.S. Federal Reserve’s work. On October 14, 1929, he was asked: “What do you think about the stock market?” By then, it had been rising for 10 years. Fisher replied that stocks had entered a path of steady growth. “We have overcome the period of crises,” he said.

Two weeks later (October 28), the market began to fall and dropped by 75% over three years. Fisher went down in history as the man who predicted a rise just before the crash. His reputation was never restored.

Jeremy Siegel is a well-known market theorist. Seventy years after Fisher’s mistake, he wrote in his book that he had done everything possible to avoid such a mistake. He analyzed the entire history and concluded that markets had entered a path of sustainable growth. This was in the spring of 2008. A few months later, the dot-com crisis began. The market did not return to the level it had been at when Siegel was writing until 2009.

LTCM was a fund created by two Nobel Prize laureates (John Meriwether and Myron Scholes) and one of the executives of Salomon Brothers. The fund was not supposed to follow the market; it was supposed to make money all the time. For several years, it performed excellently. In 1998, the fund went bankrupt, taking billions of dollars down with it. Its investors included the largest banks with powerful analytical departments.

Mary Ver (of LTCM) did not lose heart. A couple of years later, he set up another fund and went bankrupt again in 2008.

Bill Hwang (Archegos) lost more than $10 billion.

Cathie Wood (ARKK) — her fund invested in technology companies. Tech stocks have grown the fastest in recent years. Her fund managed to deliver a 77% loss to investors.

The crisis began with mortgage-backed securities. Rating agencies assigned them AAA — the highest credit rating. Pension funds bought them in huge volumes.

Why did the collapse happen? The rating agencies made a decision: the behavior of these mortgages was not correlated. Correlation was zero. What possible correlation could there be between John Smith, who bought a house in Florida, and Michael Johnson, who bought a house in New York?

On this logic, they built a diversified portfolio of millions of mortgages. The risk of each one was high, but in the portfolio it was practically zero, because they were not correlated.

The error was that when the economy turns and people lose their jobs, John and Michael lose their jobs at the same time. During crises, correlation rises to 30-40-50%. The portfolios collapsed.

It was plain incompetence. But the film "The Big Short" captures the essence: when the issue is raised, people at rating agencies get defensive and say, "Well, everyone does it."

Ording kicks in — a psychological bias in which everyone acts the same way and no one speaks out against it, because they are afraid of being fired. Plus greed — we believe in positive outcomes because we want to believe. Even at the level of professionals who are subject to criminal liability, this still shows up.

Mathematician Gauss came up with the normal distribution, in which likely events cluster in the center and unlikely ones at the edges (a bell-shaped curve).

There is the central limit theorem: under certain conditions, random processes are distributed within this normal distribution.

The key words are “under certain conditions.”

These conditions are strict:

• The realizations must be absolutely independent of one another.
• The process must not change over time.
• There must be certain properties.

Market processes do not have these properties. They depend on history (after all, you invest by looking at history). The distribution changes over time (new facts emerge). There is feedback: what happens in the market affects your actions and the actions of other investors.

Investors usually buy when prices are rising and sell when they are falling — this creates a non-normal distribution.

If you analyze historical market series, you can see fat tails — major changes occur much more often than Gaussian theory predicts. The central part is distorted as well.

Nevertheless, all theories (Value at Risk, classical return and volatility models) are ultimately based on the normal distribution. This introduces an error into the very core of financial theory. The principle of garbage in, garbage out: a flawed theory produces flawed answers.

There are three modes on investment markets, and they work differently.

Gambling.

This is the mode in which most investors operate. You are betting on the direction of the market without any edge. The probability of winning is roughly 50%. Either you guessed right, or you didn’t.

The problem is the asymmetry of returns: +5% and -5% do not cancel out to one; the result is less than one. One bad large move can wipe out more than you earned previously.

Macro investing.

This is investing based on macroeconomic processes. Not in a specific security, but in directions: whether gas prices will rise or fall, what the interest rate will be, and where currency values will go.

Results in the 21st century are worse than in equity markets. But they are much more consistently positive. The direction of major macroeconomic processes can be predicted better if you have experience and knowledge.

Good macro managers have earned 6-7% this century, while the S&P has returned 9%. But it is a more stable process, not gambling, and it is based on knowledge.

Investing Based on an Edge.

This works if you understand the niche better than the market does. For example:

• You are a major specialist in U.S. biotech, have worked in pharma, and have built startups. You understand what is happening at the FDA. You can invest better than the market.
• You have powerful IT systems (like Medallion or Apollo). You can compute faster and on a larger scale. You get better results.
• You write an algorithm and think it will work? There is a >50% chance it won’t. You have no edge.

Investing based on an edge delivers stable results. It is not always better than the index (the market can surge sharply on concentrated sectors), but it is significantly less random.

When you look at successful investors, you need to remember the survivor bias in its statistical form.

Flip a coin 1,224 times — one person will guess correctly 10 times in a row. In a market with 10,000 funds, roughly 10 should randomly guess the direction correctly for 10 years in a row. Those who guess poorly leave the market. Only the winners remain.

When you see a fund with 10 years of strong performance, you are seeing the result of random selection and combination. That does not mean the method works.

Ray Dalio (Bridgewater) delivered +1% versus the S&P over the 21st century. A strong result. But if you take the period from 2004 onward (skipping the first three years of the century), his fund underperformed the S&P by an average of 4% per year. All of his outperformance came in the first three years. After that, he was losing money.

Student’s t-test will not show that this was not random.

Buffett built his business on cheap money (the insurance business) and on the ability to obtain more information about the market than other participants. Initially, he outperformed the market. As the market became more complex, the quality of his investments declined. In the 21st century, he has consistently underperformed the S&P. The company is now sitting in cash.

Soros made a lot of money by manipulating markets (the pound, silver) — at the time, this was still allowed. Later, he lost a lot of money, for example in Russia. He has not shown any fundamental investment results.

Ralph Prechter (Elliott waves) — his forecasts were correct in 17% of cases. By chance, it would be 50%.

Bitcoin rose from $20,000 to $126,000 (currently around $70,000). More than threefold up.

MicroStrategy invests investors’ money in Bitcoin. The company’s portfolio is in the red.

How so?

The bulk of the money comes to investors when an asset rises very sharply. When it falls, investors scatter and the money flows out.

The Money-Weighted Return (MWR) chart — what the average investor actually received — shows that large sums came in at the peaks and then flowed out when Bitcoin slumped. Most of the money was invested above 100,000 and above 60,000.

The average Bitcoin investor lost money. Bitcoin tripled, but people lost money.

It mirrors the entire market. The average person invests at the peaks, when everyone thinks it will take off. And sells at the lows.

SpaceX is planning an IPO on June 12. It’s a compelling story: Elon Musk, space, data centers. It’s well-packaged gambling.

Why? If you were asked why to invest, you would say: “I think it will be popular, the price will go up.” But that is gambling — you have no other reason.

The IPO problem: the reaction to affirmative action (when everyone wants to buy) lasts only a very short time — from minutes to hours. The allocation is limited.

Even large investors with $500 million under management will receive only 1-5% of what they ask for. Demand exceeds supply. The price rises.

But if you fail to sell within 2-3 hours after the IPO, you will lose money. Everyone who wanted in has already bought. Then selling has to start — and the price falls.

The statistics are clear: on average, IPOs lose money within months.

Facebook’s IPO was exactly the same. At the IPO, people made money and sold immediately. Then there was a pullback. After that, Facebook became a normal company.

Barron’s (a major online magazine) wrote in 2012: “The fair value of Facebook is $15.” Today, Facebook is trading above $600.

On the subject of market forecasting.

What matters is not what is true about the company, but what the market will think after some time.

A company may be fundamentally sound, but if the market thinks it is bad, the price falls. You will not make money, even if you are theoretically right.

Or, conversely: Tesla is insanely overvalued, and it is unclear why it should generate such returns. But it has been doing so for so many years because the market does not think that way. There is hype, fashion, belief, advertising.

If you follow fundamental ideas without taking into account what the market will do, you will lose. The market is the market — it has its own laws and its own lawlessness.

Tesla’s anomalous rise is irrational. For many, it shattered the belief that there are fundamental reasons (P/E ratio, etc.) that determine the price.

P/E as a valuation multiple is an interesting one. It has been used for 100 years, but it has never worked and does not work. If you plot different P/E multiples against future growth, there is no correlation.

If you want to earn consistently in the market, you need either to:

• Have an informational edge (you understand the niche better than the market does).
• Have a technological edge (you can calculate faster, more, and more accurately).
• Be very good at understanding macroeconomic processes.

If you have none of these, you’re playing in a casino with odds close to 50%.

Investing in an index over the past 20-23 years has delivered good results. But that does not mean it will do so over the next 20 years. No one knows that. That is gambling too — you are betting that the market will not change.

If you want to do something meaningful, invest based on an edge or on a solid understanding of macroeconomics.

In this market, you need to be more skeptical than trusting. But those who demonstrate an edge or an understanding of macroeconomic processes will earn more consistently than the rest.