A study of the dynamic portfolio adjustment model based on the Markov decision process

It is a primary concern of investors to find strategies that make their investments high in return and low in risk. This paper investigates a dynamic portfolio adjustment model based on the Markov decision process, which aims to provide investors with investment strategies with high returns and low risk. By introducing the Markov mechanism, this paper constructs a dynamic asset allocation model that utilizes the conditional capital asset pricing model to determine the asset weights under different market states. A state transfer matrix is constructed to describe the transfer probabilities between different market states. It enables investors to speculate the possible future states based on the known current market states, to make more accurate asset allocation adjustments. By introducing the Markov mechanism, this paper constructs a dynamic asset allocation model that utilizes the conditional capital asset pricing model to determine the asset weights under different market states. A state transfer matrix is constructed to describe the transfer probabilities between different market states. It enables investors to speculate the possible future states based on the known current market states, to make more accurate asset allocation adjustments. The experimental results show that the improved portfolio adjustment strategy has an annualized return of 41.03%, which is higher than the control group’s annualized return of 21.00%, and is about 2 times the control group’s experimental annualized return. The cumulative return of the portfolio adjustment strategy is 120.34%, which is higher than the cumulative return of the control group which is 54.96%, and is about 2.2 times the experimental annualized return of the control group. The Sharpe ratio of the portfolio adjustment strategy is 1.52, which is higher than the Sharpe ratio of the control group 1.09. Compared with the CSI 300 index, the annualized return of the portfolio adjustment strategy is 46.81%, which is higher than the CSI 300 index at 37.75%. The cumulative return of the portfolio adjustment strategy is 93.62%, higher than the CSI 300 index of 75.49%, and the Sharpe ratio of the portfolio adjustment strategy is 2.20, higher than the CSI 300 index of 1.35. As a result, the portfolio adjustment strategy based on the Markov decision process significantly outperforms the traditional strategy in key metrics such as annualized return, cumulative return, and Sharpe ratio, demonstrating the effectiveness of the risk diversification mechanism. The asset allocation strategy based on the MRS model further optimizes portfolio management and emphasizes the impact of market state identification on returns.