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The Effects of Experience on Investor Behavior: Evidence from India's IPO Lotteries

The Effects of Experience on Investor Behavior: Evidence from India's IPO Lotteries. Santosh Anagol , Vimal Balasubramaniam , Tarun Ramadorai Discussion by: Sergey Gelman, ICEF, Higher School of Economics, Moscow. Summary (I). Summary (II).

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The Effects of Experience on Investor Behavior: Evidence from India's IPO Lotteries

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  1. The Effects of Experience on Investor Behavior:Evidence from India's IPO Lotteries Santosh Anagol, VimalBalasubramaniam, TarunRamadorai Discussion by: Sergey Gelman, ICEF, Higher School of Economics, Moscow

  2. Summary (I)

  3. Summary (II) • Classical finance theory assumes that preferences are constant and beliefs are slow changing • New empirical evidence: investor experience seems to change risk attitude • problem: experience is endogenous • This paper shows • Experience changes investor preferences with regard to risk (and the choice of assets) • Quasi-experimental design with experience assignment

  4. Summary (III) • Data & design • 1.5 mln investor accounts; oversubscribed IPOs in India • Share allotment is performed through a lottery • Results • Treated investors are more likely to • Participate in further IPOs • Trade other stocks • Get more diversified • Realize gains • Treatment effect is moderated by “age”, wealth, bid size

  5. Comments (I) • Very convincing results • Impressive data analysis • Thorough robustness checks. Main results hold for • “Age” groups • Wealth groups • Application size groups • Interesting read!

  6. Comments (II) • Needs better explanation: • How does positive IPO experience change risk aversion? • Decreases RA: IPO participation ↑, sector weight ↑, trading ↑ • Increases RA: realization of paper gains ↑, diversification ↑

  7. Comments (III) • Closer look at: experiment heterogeneity and self-selection • “Gamblers” vs. “committed investors”

  8. Comments (III) • Self – selection: average propensity is treated with fixed effects • But what about treatment effect heterogeneity?

  9. Comments (III)

  10. Comments (III) • experiment heterogeneity and self-selection: • Cluster standard errors by experiment or at least share category (may be even use SUR to calculate s.e.)

  11. Comments (III) • Explain heterogeneity: • Pure gambling • Or forced gambling (budget constraints)? • Control for portfolio size, “age” (also include interaction terms)

  12. Comments (IV) • The questionofgeneralisability – investorstakingpart in IPO‘sarepossibly riskier thantradingonly on secondarymarket • Are theresultsdrivenbycrisisyears? Ifyouhaveparticipated in crisis, youwouldhavepossibly ….? Year x treatment?

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