Order Reduction for Higher Order Markov Chain Model and Its Application
Teng‐Zhong Rong, Xiao Zhi · 2013
An order reduction model for the higher order Markov chain based on reconstruction state space is proposed in this paper.Through theoretical analysis,it shows that the new Markov model can describe not only the behavior of the traditional higher order Markov chain model,but also more subtle random structure.After that,the newly reduction model is apphed to empirical analysis of the stock index to inherent volatility of the stock market structure.The higher order Markov property is proved and the order selection is further discussed.Finally the short and long forecasts are respectively implemented based on China stock market data.