Before you start writing me hate mail, hear me out…
There are a couple of books that have taught me a lot about investors and investing and one of the books that have stood the test of time isn’t even an investment book or has anything remotely to do with financial markets. It is David Buss’ introduction to Evolutionary Psychology. It is a textbook for students, so it is not an easy read on a Sunday afternoon, but it explains remarkably well, why so many investors act the way they do in financial markets.
Take for instance Allais’ Paradox, which was first described as far back as 1953. It goes something like this:
Imagine you have to participate in two lotteries, Lottery 1 and Lottery 2. In each lottery, you have two choices. Here are the choices for Lottery 1:
Option A: Win $1,000,000 for certain (100% probability)
Option A*: A 10% chance of winning $5,000,000, an 89% chance of winning $1,000,000, and a 1% chance of winning nothing.
Which option would you choose?
Now let’s go to Lottery 2:
Option B: A 11% chance of winning $1,000,000 and an 89% chance of winning nothing.
Option B*: A 10% chance of winning $5,000,000 and a 90% chance of winning nothing.
Which option would you choose?
I will spare you the details since this is a Friday post and I am supposed to keep it light-hearted. But rest assured that from a probabilistic viewpoint, if you chose option A you should also have chosen option B and if you have chosen option A* you should have chosen option B* because these two options are identical, at least in relation to options A and B. Before your head explodes, suffice it to say that a rational investor would have chosen either options A and B or options A* and B*, but not A and B* or A* and B.
Yet, a large minority of people will choose option A (the safe gain) and option B*. The reason is that when compared to option B, option B* seems like you got roughly the same odds of winning, but if you win you win five times as much as in option B. So option B* looks more interesting. Meanwhile, in the first lottery, the chance of winning nothing is a mere 1%, yet even such a little chance of missing out on a certain gain of $1,000,000 is enough to tempt people to forego the chance of winning $5,000,000 and take the safe $1,000,000.
Obviously, investors make similar bets all the time in financial markets. Option A is essentially a bond investment, while option A* is a typical stock market investment. Option B is an income stock with steady dividends while option B* is a growth stock with no dividends but a bright future.
Note that the two lotteries have two variables each, the probability of winning and the amount to be won. If we start to play around with the probabilities and the potential gains, something interesting happens. Men and women react differently to changes in probabilities and changes in wealth or gains.
Three researchers from Southwest Jiatong University in China have asked students to play the original lotteries above (with Renminbi replacing US Dollars as currency) and then asked another group to play two slightly different lotteries in which the amount that could be won was not $1,000,000, but $1,000 and not $5,000,000 but $5,000. So, the potential gain in wealth was a thousand times smaller than in the original lotteries but everything else stayed the same. In a third setup, they then asked another group of people to play the lotteries with the original gains of one and five million but they changed the odds of winning the lottery from 10% to 20% and from 11% to 21%. Hence, they increased the likelihood of making a profit by 10 percentage points.
What they found was that reducing the amount of money to be won in the lotteries reduced the share of women who chose the riskier option B* and made more women choose the less risky option B in the second lottery. Meanwhile, for men, there was hardly any change in behaviour. For women, the difference between $1,000 gain and $5,000 gain was not worth the reduction of winning odds by 1 percentage point.
But when the researchers changed the probabilities, men reacted to the changed probabilities but women didn’t. If there was a higher probability of winning money, the men went for it, but women didn’t care.
This difference has nothing to do with men being better at probabilities or women being greedier but it shows the evolutionary roles of men and women in most (though not all) tribal societies of our ancestors. In most primitive societies the job of men is to hunt, and hunting is essentially the same as playing a lottery. What the men care about is winning the lottery because that means bringing home food, even if it is a little bit of food that feeds the family only for a day. So anything that increases the odds of winning the lottery is a welcome incentive to play the lottery.
Meanwhile, women were typically tasked with keeping the family together and providing safety in the form of shelter, care, and food on the table. Thus, they were mostly focused on maximising resources because if you have more resources, you could better care for your children and other family members. As a result, women count the money and they are more focused on getting more resources even if that means accepting lower probabilities of winning.
So there you have it, men and women act differently in situations with uncertain outcomes but while men are trying to optimise their odds of winning, women are trying to maximise wealth.
Your light-hearted piece provoked some heavy thinking! Let‘s assume, just for fun, that the test-subjects pursue the highest geometric average payoff (instead of the arithmetic average). To do this, they must cheat a little and replace the payoff of zero with a very small payoff of 1 cent. The outcomes are:
A: $ 1 million
A*: $1‘023’050
B: 7 cents
B*: 6 cents
Now for the Chinese experiment with thousands, instead of millions.
A: $1‘000
A*: $1‘096
B: 3 cents
B*: 3 cents
Lastly, the geometric payoffs for the Chinese experiments with the original millions, but with improved probabilities:
A: $1 million
A*: $1‘830‘000
B: 35 cents
B*: 47 cents
Your piece suggests that women are quicker to apply the geometric average payoff than men are. I for one am happy with the evolutionary explanation: hunting can be life-threateningly dangerous, but someone had to do it, even though the path-dependent outcome does not look great, compared to foraging. It follows that evolution would favour species where the hunters are blind to the fact that they should use the geometric mean for their health-choices, not the arithmetic mean.
Mr. Klement, you're to be forgiven for referencing evolution in explaining human behavior (though the blog post doesn't really reference the mechanics of evolution at all). That seems to be the norm in modern financial literature.
But I will play the fool and challenge the entire concept of evolutionary psychology as an empirical science. It seems to me more of a philosophy based on storytelling than anything you can test or prove. I leave you with the challenge of digging all the way down to its first principles to see whether you agree. I would also be happy to refer you to some resources if you are curious.
PS, you don't need to tell anyone if your faith in the "science" gets shaken.