灰色—加權馬爾可夫鏈的研究及在股市預測中的應用
發(fā)布時間：2018-07-31 18:38
【摘要】：股市是一個部分信息已知、部分信息未知的灰色系統(tǒng)，股票價格作為其系統(tǒng)行為的主要特征量，是一個灰色量，并且由于受到公司自身經營狀況、國內經濟以及市場競爭程度等各種因素的影響，總是處于不停的波動變化之中。因而，本文嘗試把灰色預測和馬爾可夫鏈預測兩種預測方法結合起來，取長補短，并將相關分析的思想融入其中，建立灰色加權馬爾可夫鏈，用GM(1,1)模型來揭示經濟現象發(fā)展變化的某種總趨勢，而用加權馬爾可夫模型來確定現象狀態(tài)之規(guī)律，進而研究股票價格的運動趨勢，最終來預測股價未來可能的走勢。但是由于GM(1,1)模型預測的局限性，灰色加權馬爾可夫鏈只適合于短期預測，為了綜合分析股市，本文又給出了中長期預測效果比較好的加權馬爾可夫鏈預測模型，以及預測股市災變日期的灰色災變預測模型，，并進行了實例分析，如對股價的運動特征（短期、中長期）、漲落的時間周期和災變日期進行了定量分析，目的在于提供依據，使投資者在面對錯綜復雜的股市時把握時機，采取科學合理的投資策略，使收益最大化。
[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.
【學位授予單位】：河南科技大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F224;F832.51
本文編號：2156479
[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.
【學位授予單位】：河南科技大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F224;F832.51
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