Learning from Noise: Evidence from India’s IPO Lotteries

82 Pages Posted: 24 Feb 2015 Last revised: 31 Jul 2019

See all articles by Santosh Anagol

Santosh Anagol

University of Pennsylvania - Wharton School of Business - Business Economics and Public Policy Department

Vimal Balasubramaniam

University of Warwick - Finance Group

Tarun Ramadorai

Imperial College London; Centre for Economic Policy Research (CEPR)

Date Written: July 30, 2019

Abstract

We study a natural experiment in which 1.5 million investors participate in allocation lotteries for Indian IPO stocks. Randomized IPO gains cause winning investors to substantially increase portfolio trading volume in non-IPO stocks relative to lottery losers; the effects are symmetrically negative for experienced losses. These results are best explained by a model where agents learn from random experience about their own ability to operate in the market environment. Investors who have received multiple past IPO allocations show smaller responses, suggesting learning/selection moderates these responses to noise shocks.

Keywords: investor behavior, experience, investment, learning, lotteries, causal inference, India, noise trading

JEL Classification: G12, G14, D83, C9

Suggested Citation

Anagol, Santosh and Balasubramaniam, Vimal and Ramadorai, Tarun, Learning from Noise: Evidence from India’s IPO Lotteries (July 30, 2019). Available at SSRN: https://ssrn.com/abstract=2568748 or http://dx.doi.org/10.2139/ssrn.2568748

Santosh Anagol

University of Pennsylvania - Wharton School of Business - Business Economics and Public Policy Department ( email )

3641 Locust Walk
Philadelphia, PA 19104-6372
United States

Vimal Balasubramaniam

University of Warwick - Finance Group ( email )

Gibbet Hill Rd
Coventry, CV4 7AL
Great Britain

Tarun Ramadorai (Contact Author)

Imperial College London ( email )

South Kensington Campus
Exhibition Road
London, Greater London SW7 2AZ
United Kingdom

HOME PAGE: http://www.tarunramadorai.com

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

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