Ke Zhang’s research while affiliated with Nanjing University and other places

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Publications (1)


Learning, Fast or Slow
  • Article

February 2020

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107 Reads

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27 Citations

The Review of Asset Pricing Studies

Brad M Barber

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Yi-Tsung Lee

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Ke Zhang

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 than profitable traders to quit. 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. Received: March 4, 2019; Editorial decision: May 16, 2019 by Editor: Jeffrey Pontiff. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Citations (1)


... This is in line with research findings in behavioral finance that show that more frequent trading is associated with worse returns, due to the significant costs incurred from excessive trading (Barber and Odean 2000). This is especially true for day trading (buying and selling a stock on the same day), where it has been suggested that only 5% of day traders earn money in the long term (Barber et al. 2020;Jordan and Diltz 2003), a rate of profitability which is closer to gambling than traditional investing. ...

Reference:

When Vegas Comes to Wall Street: Associations Between Stock Price Volatility and Trading Frequency Among Gamblers
Learning, Fast or Slow
  • Citing Article
  • February 2020

The Review of Asset Pricing Studies