Learning from noise: Evidence from India's IPO lotteries *

• 成果类型: Article
• 署名作者: Anagol, Santosh; Balasubramaniam, Vimal; Ramadorai, Tarun
• 署名单位: University of Pennsylvania; University of London; Queen Mary University London; Imperial College London; Centre for Economic Policy Research - UK
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2021.02.003
• 发表日期: 2021
• 页码: 965-986
• 关键词: Investor behavior; experience; learning; lotteries; Causal Inference; INDIA

摘要

We study a natural experiment in which 1.5 million investors participate in allocation lot-teries for Indian IPO stocks. Investors who win the lottery and obtain IPO stocks that rise in value increase portfolio trading volume in non-IPO stocks relative to lottery losers; the effects are negative for lottery winners obtaining IPO stocks that fall in value. A model in which agents learn from random experience about their ability to operate in the mar-ket environment best explains the results. Investors who have received multiple past IPO allocations show smaller responses, suggesting that learning/selection moderates these re-sponses to noise shocks. (c) 2021 Elsevier B.V. All rights reserved.