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University of Cambridge > Talks.cam > Cambridge Finance Workshop Series > Randomized Strategies and Prospect Theory in a Dynamic Context
Randomized Strategies and Prospect Theory in a Dynamic ContextAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Cerf Admin. Cumulative prospect theory (CPT) helps explain many features of individuals’ attitudes to risk. But, as observed by Barberis (2012), in a dynamic setting the probability weighting of CPT leads to time inconsistency. It also leads to another feature which has not been considered to date – agents may prefer randomized strategies to pure strategies. In this paper we consider the impact of allowing CPT agents to follow randomized strategies. In the discrete-time, discrete-space model of gambling in a casino of Barberis (2012) we show that allowing randomized strategies leads to significant value gains. In a continuous-time, continuous-space model of Ebert and Strack (2014) we show that allowing randomization can significantly change the predictions of the model. Ebert and Strack show that a naive investor with CPT preferences never chooses to stop and gambles until the bitter end. We show that this extreme conclusion is no longer valid if the agent has a coin in his pocket. This is joint work with Vicky Henderson and Alex Tse (Warwick) This talk is part of the Cambridge Finance Workshop Series series. This talk is included in these lists:
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