The prospect theory is potentially an essential ingredient in modeling the disposition effect. However, many scholars have tried to explain the disposition effect with the help of prospect theory and they came to opposite conclusions. The purpose of this paper is to examine the impact of value function of the prospect theory on predicting the disposition effect.
Lagrange multiplier optimization and dynamic programming method are used to solve the representative investor’s optimal portfolio choice problem. Furthermore, numerical simulation is used to compare the prediction ability of different types of value function.
The authors support that the value function has a crucial role in predicting the disposition effect with prospect theory, i.e. the curvature and boundedness of the value function may influence the performance of applying the prospect theory in the disposition effect. They conclude that a piecewise negative exponential value function can predict the disposition effect, while others like the piecewise power value function may not.
Extant literature about modeling the disposition effect with the prospect theory mostly focus on the time when gain-loss utility occurs or the selection of reference point. This paper based on the value function properties provides a new perspective in analyzing the crucial role that value function has in predicting financial market anomalies.
