Losing from naive reinforcement learning: a survival analysis of individual repurchase decisions

Working paper

This paper applies survival analysis to individual trading data from a discount brokerage firm, and documents significant individual-level repurchase bias, investors' tendency to disproportionately repurchase more previously sold winners than losers. Investor sophistication and experience mitigated the bias, but generated asymmetric effects: the most sophisticated/experienced investors' tendency to avoid prior losers were almost completely eliminated, but they were still over twice more likely to repurchase prior winners. Limited attention, chasing past performance and risk-adjusted returns could not justify the asymmetry. This suggests one reason for loss from frequent trading was persistent naive reinforcement learning in repurchasing prior winners.

Authors: Jiao, P

• Publication status: Published
• Publisher: University of Oxford
• Series: Department of Economics Discussion Paper Series
• Publication date: 2015-11-18
• Paper number: 765
• Keywords: sophistication; repurchase bias; experience; reinforcement learning