The following summary was written by Frank Voisin, who regularly writes for Frankly Speaking. Recently, Frank sold four restaurants and returned to school to complete a combined LLB/MBA.Taleb uses this chapter to introduce Monte Carlo simulators which repeatedly run simulations of a scenario with the different variables changing based on their associated probabilities. By running these simulations millions of times, you can look at the characteristics of the set of results and generate incredibly useful inferences. For example, by considering the variability from the average result, you can determine the impact of randomness in the scenario being analyzed. The less variability, the more resistant the situation is to randomness.
Taleb suggests Monte Carlo simulators allow us to learn from the simulated future which is superior to learning from the past, because the past has a survivorship bias, and we also tend to denigrate the past by claiming misfortune had by others will not happen to us.
Conclusion: When considering things, think about the results of a Monte Carlo simulator - what result do you expect would occur after a million simulations and what level of variability? This will help ignore survivorship bias and prevent you from denigrating the past by saying misfortune won’t happen to you. The Monte Carlo simulator will help you clarify your thinking and make better choices.