Learning Fast or Slow?
Forthcoming: Review of Asset Pricing Studies
58 Pages Posted: 9 Dec 2014 Last revised: 12 Jul 2019
Date Written: May 28, 2019
Abstract
Rational models claim “trading to learn” explains widespread excessive speculative trading and challenge behavioral explanations of excessive trading. We argue rational learning models do not explain speculative trading by studying day traders in Taiwan. Consistent with previous studies of learning, unprofitable day traders are more likely to quit than profitable traders. Consistent with models of overconfidence and biased learning (but not with rational learning), the aggregate performance of day traders is negative, 74% of day trading volume is generated by traders with a history of losses, and 97% of day traders are likely to lose money in future day trading.
Keywords: learning, day traders, day trading, individual investors, Taiwan
JEL Classification: G01, G11
Suggested Citation: Suggested Citation
Do you have a job opening that you would like to promote on SSRN?
Recommended Papers
-
Investor Competence, Trading Frequency, and Home Bias
By John R. Graham, Campbell R. Harvey, ...
-
Investor Competence, Trading Frequency, and Home Bias
By John R. Graham, Campbell R. Harvey, ...
-
Sensation Seeking, Overconfidence, and Trading Activity
By Mark Grinblatt and Matti Keloharju
-
Talk and Action: What Individual Investors Say and What They Do
By Daniel Dorn and Gur Huberman
-
Overconfidence and Trading Volume
By Markus Glaser and Martin Weber
-
Overconfidence and Trading Volume
By Markus Glaser and Martin Weber
-
Overconfidence and Trading Volume
By Markus Glaser and Martin Weber
-
Overconfidence and Trading Volume
By Markus Glaser and Martin Weber
-
An Experimental Test of the Impact of Overconfidence and Gender on Trading Activity
By Richard Deaves, Erik Lueders, ...