Prediction of Sse Composite Index Based on the Markov Model Weighted by Macroeconomy on Sliding Window
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Conventional Markov model could be applied to the prediction of data which has no following effects. It has certain validity for stock index prediction but the changes of the stock index will be affected by macroeconomic fundamentals, while the traditional Markov prediction model does not take into account the macroeconomy. Therefore, this paper uses the three indicators of Industrial Value Added, M1-M2, and CPI to consider the macro fundamentals and weight the conventional Markov model, and then forecasts the closing price of SSE Composite Index from the 41st to the 48-week in 2019. The prediction results show that the new method can forecast the index better, and is of some reference value for investors to make decisions.
Sse composite index, Weighted markov model, Macroeconomy, Sliding window