Key Takeaways from "Fooled by Randomness"
My takeaways from "Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets" by Nassim Taleb.
On investments, the financial markets, and banking systems
Likelihood of a crisis changes: The market is very random, and inferences have a lifetime.
We take past history as a single homogeneous sample and believe that we have considerably increased our knowledge of the future from the observation of the sample of the past. What if vicious children were changing the composition of the urn? In other words, what if things have changed?
Rational investors and predictable patterns do not exist.
Robert Lucas dealt a blow to econometrics by arguing that if people were rational, then their rationality would cause them to figure out predictable patterns from the past and adapt, so that past information would be completely useless for predicting the future. We are human and act according to our knowledge, which integrates past data. I can translate his point with the following analogy. If rational traders detect a pattern of stocks rising on Mondays, then immediately such a pattern becomes detectable, it would be ironed out by people buying on Friday in anticipation of such an effect. There is no point searching for patterns that are available to everyone with a brokerage account; once detected, they would be self-canceling.
The peso problem: Currency traders are fooled by the stability of a currency.
The designation "peso problem" does not appear to be undeservedly stereotypical. Things have not gotten better since the early 1980s with the currency of the United States' southern neighbor. Long periods of stability draw hordes of bank currency traders and hedge fund operators to the calm waters of the Mexican peso; they enjoy owning the currency because of the high-interest rate it commands. Then they "unexpectedly" blow up, lose money for investors, lose their jobs, and switch careers. Then a new period of stability sets in. New currency traders come in with no memory of the bad event. They are drawn to the Mexican peso, and the story repeats itself.
Financial analyst models are broken because they remove outliers.
In most disciplines, such asymmetry does not matter. In an academic pass/fail environment, where the cumulative grade does not matter, only frequency matters. Outside of that, it is the magnitude that counts. Unfortunately, the techniques used in economics are often imported from other areas—financial economics is still a young discipline (it is certainly not yet a "science"). People in most fields outside of it do not have problems eliminating extreme values from their sample when the difference in payoff between different outcomes is not significant, which is generally the case in education and medicine.
Skewed bets: bet on a few very unlikely events, small bets, high upside.
Try to make money infrequently, as infrequently as possible, simply because I believe that rare events are not fairly valued, and that the rarer the event, the more undervalued it will be in price. In addition to my own empiricism, I think that the counterintuitive aspect of the trade (and the fact that our emotional wiring does not accommodate it) gives me some form of advantage. Why are these events poorly valued? Because of a psychological bias; people who surrounded me in my career were too focused on memorizing section 2 of The Wall Street Journal during their train ride to reflect properly on the attributes of random events. Or perhaps they watched too many gurus on television.
"In the markets, there is a category of traders who have inverse rare events, for whom volatility is often a bearer of good news. These traders lose money frequently, but in small amounts, and make money rarely, but in large amounts. I call them crisis hunters."
Short time scales will only tell you the variability of an investment, not the returns.
- Our emotions are not designed for investments.
"The dentist did better when he dealt with monthly statements rather than more frequent ones. Perhaps it would be even better for him if he limited himself to yearly statements."
- You tend to give your losses more weight than your wins. A $2 loss will annoy you more than a $2 gain will make you happy.
[The dentist] does not like volatility as it causes a high incidence of negative pangs. The closer he observes his performance, the more pain he will experience owing to the greater variability at a higher resolution. Accordingly, investors, merely for emotional reasons, will be drawn into strategies that experience rare but large variations. It is called pushing randomness under the rug. Psychologists recently found out that people tend to be sensitive to the presence or absence of a given stimulus rather than its magnitude.
- Investments observed at narrow time scales will always end up looking worse than expected. When you expect an x% return at a y% error rate, the narrower the time scale, the more random and volatile your investment will appear.
Probabilities are only one part and perspective; statistics is a powerful tool for investments, but it is bad at risk assessment.
- Confidence is more important than the data itself.
It is not the estimate or the forecast that matters so much as the degree of confidence with the opinion.
- Statistics is basically the relationship between information and confidence.
It is all based on one simple notion: the more information you have, the more confident you are about the outcome. Now the problem: by how much? The common statistical method is based on the steady augmentation of the confidence level, in nonlinear proportion to the number of observations. That is, for an n times increase in the sample size, we increase our knowledge by the square root of n. Suppose I am drawing from an urn containing red and black balls. My confidence level about the relative proportion of red and black balls after 20 drawings is not twice the one I have after 10 drawings; it is merely multiplied by the square root of 2 (that is, 1.41).
- People tend to ignore the impact of events that happen with low probability.
"Are you bullish or are you bearish?" I was asked by the strategist. I replied that I could not understand the words bullish and bearish outside of their purely zoological consideration. Just as with events A and B in the preceding example, my opinion was that the market was more likely to go up ("I would be bullish"), but that it was preferable to short it ("I would be bearish"), because, in the event of its going down, it could go down a lot. Let us assume that the reader shared my opinion, that the market over the next week had a 70% probability of going up and a 30% probability of going down. However, let us say that it would go up by 1% on average, while it could go down by an average of 10%.
"Assume I engage in a gambling strategy that has 999 chances in 1,000 of making $1 (event A) and 1 chance in 1,000 of losing $10,000 (event B), as in Table 6.1. My expectation is a loss of close to $9 (obtained by multiplying the probabilities by the corresponding outcomes). The frequency or probability of the loss, in and by itself, is totally irrelevant; it needs to be judged in connection with the magnitude of the outcome. Here A is far more likely than B. Odds are that we would make money by betting for event A, but it is not a good idea to do so."
Monte Carlo Simulations
"The Monte Carlo man's realism without the shallowness, combined with the mathematician's intuitions without the excessive abstraction. For indeed, this branch of mathematics is of immense practical use—it does not present the same dryness commonly associated with mathematics. I became addicted to it the minute I became a trader. It shaped my thinking in most matters related to randomness."
Markets are not efficient because people are biased and over/undervalue stock prices.
"Shiller made his mark with his 1981 paper on the volatility of markets, where he determined that if a stock price is the estimated value of 'something' (say the discounted cash flows from a corporation), then market prices are way too volatile in relation to tangible manifestations of that 'something' (he used dividends as a proxy). Prices swing more than the fundamentals they are supposed to reflect; they visibly overreact by being too high at times (when their price overshoots the good news or when they go up without any marked reason) or too low at others."
News is broken and actually carries low information.
- Journalism has only become faster but actually poorer in quality. News is oversharing, and there is too much information at a very low resolution.
"Media journalism is a thoughtless process of providing the noise that can capture people's attention, and there exists no mechanism for separating the two."