Recently, I’ve been rereading Taleb’s *Fooled by Randomness*. There were some things I couldn’t understand the first time I read it, but after two years, I’ve come back to it and gained much deeper insight. The book constructs a complete theoretical system of randomness, with its core conceptual framework centered around randomness, extending to key concepts such as black swan events, survivorship bias, path dependence, probability blindness, skewed distributions, and more. These concepts do not exist in isolation but form an interconnected and progressively layered theoretical network.

Within this theoretical structure, randomness is defined as an unpredictable force that profoundly impacts outcomes in life and markets, yet is often misunderstood as order or predictability. Taleb believes that randomness is a fundamental characteristic of how the world works, not a coincidental phenomenon. Through the classic metaphors of “Russian roulette” and the “monkey at a typewriter,” he vividly illustrates the essence of randomness: In the Russian roulette game, the participant has a one in six chance of dying but can win $10 million—the expected value of the game is positive, but the individual player’s time series inevitably goes to zero; while the infinite monkey typing example shows that, given enough monkeys, eventually one will randomly type out an epic, but if you only focus on this “genius monkey,” you ignore all the others banging away aimlessly.

✨ Black swan events, as an important part of the theory of randomness, are defined as events that are rare, have extreme impact, and are only explainable after the fact. Taleb vividly illustrates the destructive power of black swans through John’s story: a star trader earns $250 million over seven years, but loses $600 million in a single market fluctuation with extremely low probability. He calculated the event as a “one in 100 trillion years” occurrence, but reality doesn’t care about probability calculations. This case deeply reveals the essential characteristics of black swan events: they often fall outside the predictive scope of probability models based on historical data and have devastating impact.

✨ Survivorship bias is another core concept in Taleb’s theoretical system. It refers to people’s tendency to focus on things that have “survived” (such as success stories or existing data) while ignoring those that did not survive (such as failures or lost data), leading to one-sided or even incorrect conclusions. Taleb perfectly illustrates this concept with a case from the British Royal Air Force during World War II: statisticians found returning planes had the most bullet holes in the wings, with few in the cockpit and tail, so they recommended reinforcing the areas with no bullet holes, because planes hit in the cockpit and tail never made it back—they weren’t in the sample.

👉 In fact, those who have been trading for a long time should be able to relate to some of the points above. There are some market conditions where no matter what you do, you make money smoothly, and other times, no matter how many technical methods you use, you end up stopping out. This is very similar to the infinite monkey typing example in the book—you can’t attribute smooth trading entirely to your skills and system beating the market while ignoring the issues with losing trades. This kind of randomness is defined as an unpredictable force.

👍 A good trading system must be able to maintain positive feedback even after smoothing out a large amount of market volatility, and a good trader must be able to stay highly focused and dare to take large positions in smooth market conditions, while being able to test small positions, cut losses decisively, or even just wait and observe during tough periods. ‍#Gate广场圣诞送温暖 #btc