The MacArthur Foundation gave out its latest batch of “genius grants” yesterday, recognising “exceptional creativity in their work and the prospect for still more in the future.”
One of the winners is a CalTech economist most famous for calling traders idiots.
In 2010, Dr. Colin Camerer co-authored, “Using Neural Data to Test A Theory of Investor Behaviour: An Application to Realisation Utility.” It is his most downloaded paper, according to the St. Louis Fed.
Camerer and his co-authors found that the “realisation utility” model of investing is way more prevalent than it should be.
“Realisation utility” describes the phenomenon of a given trader being more prone to taking “realised gains,” or immediate profits, than to allow “paper gains” to linger on their theoretical balance sheet.
As they put it:
“[The ‘realisation utility’ trader is] keen to realise capital gains as soon as possible and to postpone realising capital losses for as long as possible.”
For a significant number of traders, a part of the brain that should not be given the keys, so to speak, to controlling trading decisions ends up doing so anyway more often than it should.
When that happens, this results:
“… there were a total of 495 occasions in which our subjects realised gains, and that most of these decisions were suboptimal. Given that stocks exhibit short-term price momentum in the experiment, it is generally better to hold on to a stock that has been performing well. This explains why most (77.9%) of subjects’ decisions to hold on to winning stocks were optimal, and why most (67.5%) of subjects’ decisions to sell winning stocks were suboptimal. Similarly, in the experiment, it is generally better to sell a stock that has been performing poorly. This explains why most (79.2%) of subjects’ decisions to sell losing stocks were optimal, while most (80.3%) of their decisions to hold these stocks were suboptimal.”
Here’s the chart:
The finding “stands in sharp contrast to the prediction of a simple rational trading model in which subjects maximise the expected value of final earnings.”
Camerer’s most cited paper, according to the St. Louis Fed, is his 1999 work “Experience-Weighted Attraction Learning In Normal Form Games,” which proposes an entire new way of looking at how humans learn, called “experience weighted attraction.”
Camerer and his co-author Teck-Hua Ho found this concept captures the phenomena of subjects combining belief learning and experience learning.
Camerer and his fellow “geniuses” get $US625,000 paid out over five years — not chump change to an academic!
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