Study Of Grey-Weighted Markov Chain And The Application Of Prediction In Stock Market

The stock market is a grey system, the partial information of which is knownand some information is unknown. As the main feature of the system, the stock price,is a grey and always keep in fluctuation, due to the operations of the company, thedomestic economy and the degree of the market competition, and so on. Thus, thepaper attempts to combine the Grey forecast and the Markov chain prediction andblends in the correlation analysis of the thought. Finally, we establish the Grey-Weighted Markov chain, which we use GM (1,1) model to reveal the general trend ofthe development and change of economic phenomenon, and the weighted Markovmodel determine the law of the phenomenon, then we study the movement of the stockprice, to predict the future possible trends of the stock price. However, due to theprediction limitations of the GM (1,1) model, the Grey-Weighted Markov chain is onlysuitable for short-term forecast. In order to comprehensively analyze stock market, thispaper gives a weighted Markov chain forecast model, which suits for the medium andlong term prediction, and also offer a grey disaster prediction model, which is used toforecast the date of the stock market disaster. Finally, through the empirical analysis,we quantitatively analyze the characteristics of stock price movement (short, mediumand long term), the time cycle of fluctuation and the date of disaster. The purpose is toprovide a reference for the investors when they face the complex stock market, andthey can grasp the opportunity and adopt scientific and reasonable investment strategy,so that causes the income maximization.