Trading Under Uncertainty
description
Transcript of Trading Under Uncertainty
Trading Under Uncertainty
Ankur Pareek
Yale School of Management
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
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.
Time 0No information
Time 14 traders givenNoisy info
Time 24 traders givenPerfect info
Time 3Public announcementNoisy info.announced
Time 4 or 5Dividend paidand trading ends
Timeline for a Trading Session
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
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.
S toc k P ric es and E ffic ienc y of Alloc ation for S es s ion 2
0
100
200
300
400
500
600
700
800
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77
T rade number
Pri
ce/P
erce
nta
ge
TransactionP rice
E quilibriumPrice
AllocationEfficiency
S toc k P ric es and E ffic ienc y of Alloc ation for S es s ion 3
0
100
200
300
400
500
600
700
800
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57
T ra de numbe r
Pri
ce/
Per
cen
tag
e
E quilibriumP rice
Trans actionP rice
AllocationEfficiency
Informed Partial info. Uninformed
Initial Stocks 20 20 35
Final Stocks 7 29 39
Aggregate Profit 8600 1255 5145
Profit/Trader 2150 313.75 735.00
Exante Exp Profit 3400 -280 360
Expected number of stocks 0 31 44
Informed Partial info. Uninformed
Initial Stocks 20 20 35
Final Stocks 30 15 30
Aggregate Profit 15291 17513 27196
Profit/Trader 3822.75 4378.25 3885.14
Exante max Exp Profit 5525 3400 3075
Expected number of stocks 75 0 0
Session 1 summary statistics
Session 2 summary statistics
Informed Partial info. Uninformed
Initial Stocks 20 20 35
Final Stocks 17 14 44
Aggregate Profit 5200 6500 3531
Profit/Trader 1300.00 1625.00 504.43
Exante max Exp Profit 2047.22 866.67 477.78
Expected number of stocks 0 24 51
Session 3 summary statistics
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.