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William Grove, David Zald, Boyd Lebow, Beth Snitz, and Chad Nelson did a meta-analysis (a study of studies) of 136 different studies of human experts vs. simple quant models. Here is a link to the paper by Grove et al. (2000): http://datacolada.org/wp-content/uploads/2014/01/Grove-et-al.-2000.pdf
Here is what Grove et al. discovered about 136 different studies:
- 64 clearly favored the model
- 64 showed approximately the same result between the model and human judgment
- 8 found in favor of human judgment
(NOTE: All eight cases where human judgment prevailed had one thing in common: the humans had more information than the quant models.)
Across all 136 studies that Grove et al. examined, experts were correct in 66.5% of the cases, while the quant models did significantly better with an average hit ratio of 73.2%.
Paul Meehl, one of the founding fathers of the importance of quant models versus human judgments, had this to say:
There is no controversy in social science which shows such a large body of qualitatively diverse studies coming out so uniformly in the same direction as this one… predicting everything from the outcomes of football games to the diagnosis of liver disease. And when you can hardly come up with a half a dozen studies showing even a weak tendency in favor of the clinician, it is time to draw a practical conclusion.
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Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.