The Art of Thinking Clearly and How It Applies to Investing

I read this book by Rolf Dobelli and there are many examples applied to investing. I compiled them below. Most of the below I have read it before here and there, but I guess this book compiles them all together. 

Survivorship bias:

Take the Dow Jones Industrial Average Index. It consists of out-and-out survivors. Failed and small businesses do not enter the stock market, and yet these represent the majority of business ventures. A stock index is not indicative of a country's economy. 

Clustering illusion:

Consider the financial markets, which churn out floods of data every second. Grinning ear to ear, a friend told me that he had discovered a pattern in the sea of data: 'If you multiply the percentage change of the Dow Jones by the percentage change of the oil price, you get the move of the gold price in two days' time.' ... His theory worked well for a few weeks, until he began to speculate with ever-larger sums and eventually squandered his savings. He had sensed a pattern where none existed. 

Sunk cost fallacy:

Investors frequently fall victim to the sunk cost fallacy. Often they base their trading decisions on acquisition prices. 'I lost so much money with this stock, I can't sell it now,' they say. This is irrational. The acquisition price should play no role.  What counts is the stock's future performance (and the future performance of alternative investments). Ironically, the more money a share loses, the more investors tend to stick by it. 

Overconfidence effect:

Overconfidence also applies to forecasts, such as stock market performance over a year or your firm's profits over three years. We systematically overestimate our knowledge and our ability to predict - on a massive scale. The overconfidence effect does not deal with whether single estimates are correct or not. Rather, it measures the difference between what people actually know and how much they think they know. What's surprising is this: experts suffer even more from overconfidence than laypeople do. If asked to forecast oil prices in five years' time, an economics professor will be as wide off the mark as a zookeeper will. However, the professor will offer his forecast with certitude.  

Regression to Mean:

Extreme performances are interspersed with less extreme ones. The most successful stock picks from the past three years are hardly going to be the most successful stocks in the coming three years.

Loss Aversion:

Loss aversion is also found on the stock market, where investors tend to simply ignore losses on paper. After all, an unrealized loss isn't as painful as a realized one. So they sit on the stock, even if the chance of recovery is small and the probability of further decline is large.  

Action Bias:

The action bias is accentuated when a situation is new or unclear. When starting out, many investors act like the young, gung-ho police officers outside the nightclub: they can't yet judge the stock market so they compensate with a sort of hyperactivity. Of course this is a waste of time. As Charlie Munger sums up his approach to investing: 'We've got ... discipline in avoiding just doing any damn thing just because you can't stand inactivity.' 

I particularly like this last one:

On how to have better thinking:

The pope asked Michelangelo: ' Tell me the secret of your genius. How have you created the statue of David, the masterpiece of all masterpieces?' Michelangelo's answer: 'It's simple. I removed everything that is not David.'

Thinking more clearly and acting more shrewdly means adopting Michelangelo's method: don't focus on David. Instead, focus on everything that is not David and chisel it away. In our case: eliminate all errors and better thinking will follow.