Wednesday, November 28, 2018

Loss aversion

Loss aversion is a form of an excessive self-regard. It is a tendency to prefer avoiding losses compared to getting equivalent gains. Nobel laureate Daniel Kahneman has developed this concept with Amos Tversky. Like many other psychological heuristics and biases, loss aversion can be misunderstood and used for your own good or bad.

Two forms of loss aversion

First case goes like this: Imagine a situation that you are offered a bet in which you have 50 per cent chance of winning 110$ or 50 per cent of losing 100$. Would you take this bet? According to Kahneman, most people wouldn´t take the bet. Imagine another bet in which you have a 100 per cent chance of losing 90$ or 90 per cent chance of losing 100$? Would you take the first or second bet? According to Kahneman and other researchers, most people would take the last bet. As you can see from these bets, first situation has the same probability of winning 55$ and losing 50$ and in the second situation, both bets have an expected value of losing 90$.

What this means is that in the first situation people were loss averse. They didn´t want to risk their 100$, even though they had a better chance of winning 110$. In the second situation people were willing to risk more money to get even. This can be seen as irrational behavior, at least according to Kahneman. But it is not that simple. As with everything in life, in reality, it depends on the situation. The behavior in the first situation is irrational only if your 100$ is not needed by you. It comes to path dependence. If you lose your money you won´t get a chance to get them back. You have lost your money and you cannot buy bread and butter. Path dependence is the same fact whatever the sum of money. You just cannot afford to have a chance to lose money you will need later. This doesn´t mean you shouldn´t take 100 bets that are similar to the first situation if you can afford to lose the money.

Second situation is different. You take more risks for not to lose, instead of accepting losses, you are more likely to risk more capital to gain what you have already lost. This makes you more vulnerable to get hurt in the long run in many ways. For example, you lose some of your money in investing a stock x, when it announces bad financial report. You are more likely to invest more money for this stock to gain your losses back than putting your money to stock y that has risen in the same time after a good financial report to get them back. Throwing good money after bad money will more likely to be a bad decision. This doesn´t mean it is always a bad decision. It is only a more probable effect. When you do this kind of mistake, you are more likely to lie to yourself about it. Instead of admitting failure by taking responsibility about your mistake, you might explain it with bad luck, or mistakes from other people, etc.

Loss protecting products and services

The providers of financial products and services use loss aversion for their advantage. Insurance is one type of products that takes loss aversion for service provider´s advantage. When you insure your fortune to protect yourself against losses, you pay the price for it. Insurance selling companies have large databases of their customers and the likelihood of getting into accidents. They know the probabilities of these accidents. And they price their insurances in a way that the value of your expected loss is smaller than the price of their expected gain from the insurance. As with the first type of loss aversion, you have to buy the insurance if you cannot afford the cost of the accident. Financial industry is also willing to sell you products that have capital protection. There is always price to pay. It can be something like a decreasing possibility for gaining capital or a bigger commission for buying the product. Whatever it is, it is not a free lunch. You have to pay for it. Be aware of anyone you tells gives you a guarantee that you cannot lose without having costs. He is not telling the whole truth about the product.

Until next week!

-TT

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