I don’t remember from where I picked up a recommendation for this book but what a great investment buying this turned out to be. It will not be an exaggeration to say that I really enjoyed this book. It was indeed informative but what made it enjoyable was how easily the transition was between points - concepts supported by anecdotes, stories and research studies and how beautifully in the end they all tie together to frame a powerful, optimistic call to action. The author’s work does make him sound like a good professor. 😃
The book is a collection of a lot of interesting concepts -
It talks about how human behavior, emotions influence our financial decisions. It is one of the reasons why the Efficient Market Hypothesis(E.M.H) doesn’t hold true.
It does critique E.M.H and provides two strong points -
If the market is really efficient with all the info priced in then what’s the point for any investor to do some work getting new info or numbers when everything is already priced in ?
Also, if the market is really efficient with all the info priced in then how come George Soros’, Jim Simons’ and Warren Buffets of the world have made billions of dollars?
It gives a good glimpse on how the concept of “money” has not been around forever and is relatively recent on an evolutionary scale. So the idea of losing money generates similar emotions as “fight or flight” in case of a physical attack.
Using advanced technologies such as fMRI it has been found that similar centers in the brain are activated when there are prospects of making/losing money.
Humans are not rational beings and are influenced by emotions of fear, panic and pleasure and thus that is what makes them take irrational decisions in the context of money.
Concept of probability matching with the help of an experiment:
Consider the game Psychic Hotline. Either letter A or B will be shown on the screen. If you get it right +$1 else -$1.
After a few rounds, the participants observe that A appears more often than B. Say 75% of the times it is A, and B appears 25% times.
So the optimal strategy is to always pick A.
But people try to mix it up which is called “Probability Matching” and
that is sub-optimal thus reducing the earnings to only 62.5%
times.
- It is definitely worth pondering that our DNA is 97% similar to an orangutan but the 3% difference is big enough to keep us on different sides of the fence.
- Emotion isn't the source of irrationality. The author's proposition is that we wrongly conclude that emotions are the reason for our irrational actions when infact they are the reason of rationality.
- The author reminds us that although there were so many attempts to draw inspiration from Physics to apply to Economics - it is infact more similar to Biology. Both are equally complicated fields.
- The author puts forward a new theory to beat the E.M.H. He talks of Adaptive Market Hypothesis.
This theory is about revolving around heuristics. It blends in the concept of "bounded rationality" too. A very good example of this is how we may have 10 shirts, 10 pants, 5 ties and 5 jackets. We don't try out every single of them every day before going to work. Because in our minds already have a heuristic/idea about which shirt will shirt well enough with a pant.
- Also, going by the word "adaptive" we continue to adapt and learn from our experiences and surroundings (dressing appropriately is an example - while going to a function we don't try out running shorts - adapting and cutting down our choices. This is another example of bounded rationality).
The example that blew my mind was around Biological Evolution. It was fascinating to see how the concepts of risks - system
ic and idiosyncratic can be tied to evolution.
Here's my attempt to summarize it -
Let's say a hypothetical creature which could produce only 3 offsprings (Tribble) has a choice to dwell on a plateau or a valley. Odds are such that in the
a) Valley - 3 offsprings are guaranteed.
b) Plateau - 50% chance for 2; 50% chance for 4 offsprings. Net being still 3.
Now if everyone of the tribble chooses to live in the valley - they will be safe from sunshine but not from floods. If everyone of the tribble chooses to live in the plateau - they will be safe from the floods but not from sunshine.
So which option should they choose?
Let, f be probability of choosing the valley.
1-f be probability of choosing the plateau.
Here, even though more tribbles chose to nest in the valley - all of them would be wiped out as soon as there is a heavy rainy season. So, what should be the optimal percentage of tribbles residing in a valley. This is where the principle of Probability Matching ties back in. f should be same as the probability of the sunlight. By probability matching, the reproductive bets will be hedged so that the expected number of offspring will be same, no matter whether it rains or shines. Sparing the complex maths behind it, so you've to trust this!
Another variation of this would be - every tribble family have their own individual experiences ie microclimate. Each family faces rain or shine in a separate and independent toss of a coin that is something like sunshine 75% of the time and rain 25%.
So the probability that all of them (say 10 tribble families) will be washed away is (1/4)^10 i.e 1 in a million. Basically, nature has diversified the risk of extinction via microclimates i.e diversification is necessary in an evolutionary cycle. It also explains why dinosaurs got extinct cause they didn't hedge their bets - they were all on one planet and got wiped out together when a meteor hit. Similarly, you can also argue why it's important for humans to inhabit some other planet too!
I thought this was a very cool thing I learned!
Something that gave me lot of optimism was how finance can actually help fund researches for life saving drugs or even the current Covid-19 crisis. We all are aware how governments are cutting funding for health and research. A cancer drug research takes 10 years and $200 million with a 5% chance of success. Clearly, no private investor would want to put their money in such a venture where they would lose their money 95% of the time. They would rather fund a tech startup and sell to FAANG later.
Better approach is to invest rather one project at a time than to invest in 150 such research projects. Even with 5% chance of success - you can to do the math to see that it is promising that atleast 3 of them will succeed. Now, the crucial part is funding $200mn x 150 i.e $30billion. Here's where you can issue bonds and finance more than half of the projects with long term debt; the intellectual property of 150 projects can be the collateral. And if you get fancy you can use derivatives - securitization, CDOs, Credit Default Swaps. Insurance companies can be invited to buy them too and it'd be a way for them to hedge their bets too considering they use an ugly term called "longevity risk". This $30 billion cancer bonds market will still be way smaller than the housing market. I wrote earlier here how this same principle can be used to fund Covid-19 research as well. I'm still waiting to come across a logical argument of why this is not a feasible way to cure diseases like Cancer!
Overall, this was a fantastic book and worth my time reading during the lockdown. Hope it excited you to give it a try as well.
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