Consumption and Investment Portfolio Problem Under Distributional Uncertainty Using Bayesian Methods

In complex markets, limited information makes it difficult for investors to accurately estimate true distribution of the risky asset return, which reducing model robustness. This paper focuses on the consumption investment problem under risky asset return distributional uncertainty. By integrating distributional uncertainty with Bayesian methods, the paper constructs a robust model. Using the Minimax principle and dynamic programming, the paper derives explicit solution strategies under the CARA utility function by solving a minimax optimization problem. Empirical analysis verifies the rationality and effectiveness of the proposed model.