灰色—加權(quán)馬爾可夫鏈的研究及在股市預(yù)測中的應(yīng)用
[Abstract]:The stock market is a grey system with known partial information and unknown part information. Stock price, as the main characteristic quantity of its system behavior, is a grey quantity, and because of the company's own operating condition, The influence of various factors such as domestic economy and market competition is always in constant fluctuation. Therefore, this paper attempts to combine the grey prediction and Markov chain prediction, learn from each other, and incorporate the thought of correlation analysis into it, and establish grey weighted Markov chain. The GM (1) model is used to reveal the general trend of the development and change of economic phenomena, while the weighted Markov model is used to determine the law of phenomenon state, and then to study the movement trend of stock price, and finally to predict the possible trend of stock price in the future. However, due to the limitation of GM (1K1) model, grey weighted Markov chain is only suitable for short-term forecasting. In order to analyze the stock market comprehensively, this paper gives a weighted Markov chain forecasting model with good effect in the medium and long term forecasting. The grey catastrophe forecasting model for predicting the date of stock market catastrophe is also given. Examples are analyzed, such as the characteristics of stock price movement (short, medium and long term), the time period of fluctuation and the date of catastrophe, in order to provide the basis. In the face of the complicated stock market, investors can seize the opportunity and adopt scientific and reasonable investment strategies to maximize the returns.
【學(xué)位授予單位】:河南科技大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2012
【分類號】:F224;F832.51
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