The Black Swan: The Impact of the Highly Improbable - Book Review

“Several years before the financial crisis descended on us, I put forward the concept of “black swans”: large events that are both unexpected and highly consequential. We never see black swans coming, but when they do arrive, they profoundly shape our world: Think of World War I, 9/11, the Internet, the rise of Google.

In economic life and history more generally, just about everything of consequence comes from black swans; ordinary events have paltry effects in the long term. Still, through some mental bias, people think in hindsight that they “sort of” considered the possibility of such events; this gives them confidence in continuing to formulate predictions. But our tools for forecasting and risk measurement cannot begin to capture black swans. Indeed, our faith in these tools make it more likely that we will continue to take dangerous, uninformed risks.”

Nassim Nicholas Taleb

Taleb is the Dean’s professor in the Science of Uncertainty at the University of Amherst. His book The Black Swan: The Impact of the Highly Improbable talks about one observation that can negate a general observation.

The Black Swan he notes is an outlier, that lies beyond the average outcome. It’s impact is extreme and finally despite its outlier status we as humans convince ourselves that we had somehow accounted for it.

The book primarily discusses why we have this blind spot with respect to large deviations in randomness. The book has a great readability quality, never boring always making you stop and think.

Take this passage for instance:

“But we act as though we are able to predict historical events, or even worse, as if we are able to change the course of history. We produce thirty-one projections of social security deficits and oil prices without realizing that we cannot even predict these for next summer – our cumulative prediction errors for political and economic events are so monstrous that every time I look at the empirical record I have to pinch myself to verify that I am not dreaming. What is surprising is not the magnitude of our forecast errors, but our absence of awareness of it. This is all the more worrisome when we engage in deadly conflicts: wars are fundamentally unpredictable (and we do not know it). Owing to this misunderstanding of the causal chains between policy and actions, we can easily trigger Black Swans thanks to aggressive ignorance – like a child playing with a chemistry set.

Our inability to predict in environments subjected to the Black Swan, coupled with a general lack of awareness of this state of affairs, means that certain professionals, while believing they are experts, are in fact not. Based on their empirical record, they do not know more about their subject matter than the general population, but they are much better at narrating -or worse, at smoking you with complicated mathematical models. They are also more likely to wear a tie.”

The book, the author tells us flows from the literary to the more specific. Part one deals with psychology, while part two and part three deal with natural science and business.

The first part discusses our perceptions often distorted, of both historical and current events. Part two details our errors with regards to the future and the limitations of exact sciences. In ‘Those Gray Swans of Extremistan” or part three, the author delves deeply into extreme events.

Let me leave you with yet another stunning passage from the book, in the context of the largest market drop in history. (1987)

“Alexis called to tell me that his neighbor committed suicide, jumping from his upper-floor apartment. It did not even feel eerie. It felt like Lebanon, with a twist: having seen both, I was struck that financial distress can be more demoralizing than war. (just consider that financial problems and the accompanying humiliations can lead to suicide, but war doesn’t appear to do so directly).”

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.