Testing the Fractal Market Hypothesis with the Markov Regime Change Model: A Possible Combination and Convergence

The importance of predicting and knowing the future in order to plan and formulate economic strategies is not hidden from anyone. The accuracy of forecasts is one of the most important factors in choosing the type of forecasting method. The stock price index is one of the effective variables in economic systems that these very complex time series are usually assumed to be random and as a result their changes are assumed to be unpredictable. Such time series variables have the property that the shock to the variable takes a long time to disappear due to the possibility of long-term memory. The aim of the present study was to test the fractal market hypothesis with the Markov regime change model with a possible combination and convergence in the Tehran Stock Exchange. In this paper, the amount of long-term memory and stability of financial time series resulting from the total stock market index for the period 1388-1386 were examined. For this purpose, first the existence of long-term memory was examined, then the fractal nature of the market was examined using the Harst view index. The results indicate the existence of long-term memory in this variable. In this case, with one differentiation, it becomes more differentiated, so the stock price index series in Iran has long-term memory and the effects of each shock on this variable due to its long-term memory remain for long periods. It stays. The results also showed that the overall stock market index is fractal.