Abstract
Applying prospect theory (PT) in a dynamic context brings new challenges. We study PT agents facing optimal timing decisions and consider the impact of allowing them to follow randomized strategies. In the discrete model of casino gambling of Barberis (2012) we show that allowing randomization leads to gains in PT value. In the continuous analog (Ebert and Strack (2015)) we show that allowing randomization can significantly alter the predictions of the model. Ebert and Strack show that a naive investor never stops. We show that allowing naive PT agents to use randomized strategies leads to predictions which are closer to reality and include voluntary cessation of gambling.
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