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Trading Under Uncertainty Ankur Pareek Yale School of Management.

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Presentation on theme: "Trading Under Uncertainty Ankur Pareek Yale School of Management."— Presentation transcript:

1 Trading Under Uncertainty Ankur Pareek Yale School of Management

2 Motivation To study the interaction between arbitrageurs and uninformed investors and measure the ex-ante allocation efficiency of the market. Provide some insight into validity of some of the theories behind the dotcom bubble: –Ofek and Richardson(2003)- short sales restrictions with heterogeneous beliefs explain the internet stock bubble –Pastor and Veronesi (2006)- high uncertainty in future earnings growth rate explained the existing prices of tech stocks in late 90s –Lamont and Stein (2004) – less arbitrage capital for short-selling in rising overvalued market Understanding the behavior of arbitrageurs under uncertainty

3 Experimental Design Create market for stocks of a technology firm Sysco which is based on single technology still in R&D phase Three sets of traders with different information sets –Arbitrageurs with perfect information about the final dividend realization –Traders with partial/noisy information about the final dividend. –Uninformed traders Arbitrageurs faced with uncertainty about when the arbitrage window will close (end of period 4 or period 5) Three sessions with 4 or 5 periods which vary in final dividend and signal received by partially informed traders.

4 Time 0 No information Time 1 4 traders given Noisy info Time 2 4 traders given Perfect info Time 3 Public announcement Noisy info. announced Time 4 or 5 Dividend paid and trading ends Timeline for a Trading Session

5 Experimental Results Prices did not converge to fundamental values when there was overvaluation in the market in session 1 and session 3 –Consistent with Ofek and Richardson (2003): short sell constraints and heterogeneous beliefs Traders with noisy private information trade on it aggressively immediately after receiving it but don’t trade on it or reverse some of their trades later Prices converge close to fundamental value when dividend is high

6 Experimental Results (contd’) Arbitrageurs did not sell all their securities before the end of period 4 in low dividend sessions 1 and 3 –Action inconsistent with risk aversion/ risk neutrality of arbitrageurs. –Can be explained by risk loving preferences like prospect theory with convex utility over losses w.r.t some benchmark target profit Arbitrageurs did not indulge in speculative behavior in most of the cases.

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10 InformedPartial info.Uninformed Initial Stocks20 35 Final Stocks72939 Aggregate Profit860012555145 Profit/Trader2150313.75735.00 Exante Exp Profit3400-280360 Expected number of stocks03144 InformedPartial info.Uninformed Initial Stocks20 35 Final Stocks301530 Aggregate Profit152911751327196 Profit/Trader3822.754378.253885.14 Exante max Exp Profit552534003075 Expected number of stocks7500 Session 1 summary statistics Session 2 summary statistics

11 InformedPartial info.Uninformed Initial Stocks20 35 Final Stocks171444 Aggregate Profit520065003531 Profit/Trader1300.001625.00504.43 Exante max Exp Profit2047.22866.67477.78 Expected number of stocks02451 Session 3 summary statistics

12 Conclusion Heterogeneous investors combined with short-sales constraints could lead to persistence of overpricing. Perfectly informed arbitrageurs more risk-loving compared to investors with noisy information sets. –Investors with partial information risk-averse as shown by their trading behavior. –Arbitrageurs risk taking in final period can only be justified by risk-loving behavior Difficult for under pricing to persist in a market with arbitrageurs with perfect information. Future experiments could help in resolving the debates about the existence and reasons behind the dot-com bubble of 1990s.


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