stock portfolio with maximum predictability of sharpe ratio based on hidden markov model

The sharpe ratio is one of the performance evaluation criteria of the stock portfolio, which shows the return per unit of risk. this ratio is particularly important for risk-averse investors. in the current research, the hidden markov model approach introduces a new stock portfolio model called the maximum predictability portfolio of the sharpe ratio. the hidden markov model used for each hidden state has a mixture of normals distribution output, which is used to calculate the return and standard deviation to calculate the sharpe ratio in the investment horizon. the research portfolio calculates the weights of the portfolio in such a way that the sharpe ratio is maximized in the horizon of the portfolio. the optimal research portfolio was optimized using the historical data of 10 indices from the tehran stock exchange between 2018 and 2018 in a four-member mode space. the evaluation of the performance of the optimal portfolio in the sharpe ratio criterion shows that the research model has a better performance than the mean-variance model and the equal-weight model.