An important book for anyone looking to get better at decision making. Its central premise is that we must accept the fallibility of our judgement if we want to come to more accurate predictions.

The first part of the book deals with our flaws in analysing information and making predictions. Unsurprisingly, the list of poor predictions by humans is quite long. Anyone interested in this book probably understands the issues, so more evidence seems to be not so necessary as long as you understand that our judgement is far from perfect.

Hence, the second part of the book is much more useful, in my view, as it provides a solution to the problem. The solution offered by Nate Silver is to use the

The English mathematician Bayes worked out a formula in the XVIII century to estimate the new probability of an event if you receive certain evidence. I would quote the author's example directly from the book as it is so vivid that understanding complex math becomes quite easy:

*"Suppose you are living with a partner and come home from a business trip to discover a strange pair of underwear in your dresser drawer. You will probably ask yourself: what is the probability that your partner is cheating on you? … Bayes's theorem, believe it or not, can give you an answer to this sort of question - provided that you know (or are willing to estimate) three quantities:*

1

You need to estimate that the probability of the underwear's appearing as a condition of the hypothesis being true - that is, you are being cheated upon **(Y)**.

2

You need to estimate the probability of the underwear's appearing conditional on the hypothesis being false. If he isn't cheating, are there some innocent explanations for how they got there **(Z)**?

3

Most important, you need what the Bayesians call a prior probability (or simply a prior). What is the probability you would have assigned to him cheating on you before you found the underwear **(X)**?

Nate Silver also discusses making investment decisions on a stock market a few times in this book. Unfortunately, his verdict is that it is very hard to outperform the market without having some unique edge.

- Importance of continuous updates of your beliefs to move closer to the truth as opposed to seeking one single moment when you discover the full. The reason such a method of incremental steps is preferred has to do with our understanding of reality which is an approximation of the truth.

- It is worth paying attention to a market consensus as it is often correct. However, there are cases when it is not the case and the further you move away from consensus, the stronger your evidence has to be.
*"This attitude…will serve you very well most of the time. It implies that although you might occasionally be able to beat markets, it is not something you should count on doing every day; that is a sure sign of overconfidence".*

- There is another thought related to the previous idea about the challenges of running an asset management business based on active asset management. It is hard to justify charging your fees if you are not actively buying and selling stocks.
*"…markets are usually very right but occasionally very wrong. This, incidentally, is another reason why bubbles are hard to pop in the real world. There might be a terrific opportunity to short a bubble or long a panic once every fifteen or twenty years when one comes along in your asset class. But it's very hard to make a steady career out of that, doing nothing for years at a time".*

- The book also refers to the work of 'giants' in this field including Kahneman, Tversky, Tetlock and others. One message concerning Kahneman is about mistakes we make using mental shortcuts (heuristics) which implies that using special tools, checklist and following rules is very important in making decisions. Another important message is about the difference in the quality of prediction and quality of result suggesting not to judge the former by the latter. This idea was discussed in more detail by Annie Duke in several of her books.

- The idea that I read about in Philip Tetlock's
**book**about group forecasts is also discussed by Nate Silver. He points out that an average forecast is better than most individual forecasts as long as they were made independently. However, he also says that there could be instances when one individual forecast is better than the average so it may pay off to follow one particular forecaster (Think Warren Buffett in investing?).

I searched for more resources on the Bayesian theory and did some tests to be sure I had fully grasped the concept. It still looks quite complex and is worth practising this method more.

I would not say this is a must-read book. If you have mastered the Bayesian method, are familiar with the works of Tetlock and Kahneman - then probably this book will add little new to you. Having a very poor understanding of the Bayesian method, I was very glad to have read the book.