. . . fear of the unknown and our desire for certainty lead us to throw ourselves into the arms of perceived ‘experts’ ... We trust quantitatively flavoured constructs to escort us away from the gloomy reality of unmeasurable uncertainty.Pablo Triana in his new book Lecturing Birds on Flying, on the role of quantitative financial models in global finance, as reviewed in today's FT
2 comments:
The human mind has a great need to “understand” the world. The phrase “I don’t know” is a sign of weakness. The most extreme example I’ve seen was a man who had the left side of his brain surgically separated from the right side. When one side of his brain performed some action that the other side could not see, the observing side would create some explanation for what happened; with absolutely no information.
Speculation in financial markets such as complex derivatives used to be constrained by the reluctance of people to risk money on transactions they didn’t understand. Then along came the deterministic computer models that purported to assign simple risk numbers to even the most complex financial package of derivatives. The neatly packaged risk number satisfied the need to understand. Oops, that’s going leave a mark on the national debt.
When my software development team encountered an unexpected action they were inclined to sit and speculate until something occurred to them that explained the unknown action. I’m sure that they got tired of me saying “stop speculating and start testing”.
I believe that the success of my software was because it was not deterministic but kept score on how certain/uncertain the analysis might be. But then I don’t know for sure.
I would argue that in general people do not trust models determined by communities of experts; especially when the model results do neither follow empirical trends nor their own experiences.
At least I can say that of the "adapters" that I deal with every day. If we can't know anything else about the future and economic models are not really predictive, it seems that we know how to muddle through even though climate models are equally not predictive.
The only people who seem to be unsatisfied with this worldview are those who want research funding because those individuals believe that more predicted information is useful regardless of the correctness of the prediction. The conflict of interest involved takes my breath away. It seems to me that the science community tends to be uniquely non-introspective about such matters and the journalism community is remarkably reticent about asking the hard questions.
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