Relative growth rate optimization under behavioral criterion

TL;DR

This paper extends the classical growth optimal portfolio problem to a behavioral setting with prospect theory and probability distortion, deriving a closed-form solution and analyzing how benchmark growth influences investment behavior.

Contribution

It introduces a new model for relative growth rate optimization under behavioral preferences with probability distortion, providing a closed-form solution and insights into investment stability.

Findings

Benchmark growth rate significantly affects investment behavior.

High risk tolerance and adverse market states lead to distinct investment patterns.

Optimal wealth is more stable and less sensitive to pricing kernel than previous models.

Abstract

This paper studies a continuous-time optimal portfolio selection problem in the complete market for a behavioral investor whose preference is of the prospect type with probability distortion. The investor concerns about the terminal relative growth rate (log-return) instead of absolute capital value. This model can be regarded as an extension of the classical growth optimal problem to the behavioral framework. It leads to a new type of M-shaped utility maximization problem under nonlinear Choquet expectation. Due to the presence of probability distortion, the classical stochastic control methods are not applicable. By the martingale method, concavification and quantile optimization techniques, we derive the closed-form optimal growth rate. We find that the benchmark growth rate has a significant impact on investment behaviors. Compared to Zhang et al where the same preference measure is applied to the terminal relative wealth, we find a new phenomenon when the investor's risk tolerance level is high and the market states are bad. In addition, our optimal wealth in every scenario is less sensitive to the pricing kernel and thus more stable than theirs.