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Markov Chain Combination Prediction Model and Its Application in Stock Market

机译：马尔可夫链组合预测模型及其在股票市场的应用

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摘要

Markov process is a very important means to describe dynamic stochastic phenomena. First, Markov chain median value prediction method and Markov chain level Characteristic value method are introduced. Based on these predictions, the thought and steps of the combined prediction model are given. Secondly, in the part of empirical research, this paper uses Markov chain combined prediction model to predict the stock price of China railway in China's stock market and obtain the predicted value of the combination. Compared the predicted value with the predicted value obtained by other single methods, the combined predicted value is more accurate., thus it is concluded that combined forecasting method is superior to other Markov prediction method, and enrich the theory of Markov chain prediction system, it also manifests the combination of prediction and Markov chain prediction method has a strong suitability.
机译：马尔可夫进程是描述动态随机现象的一个非常重要的手段。首先，介绍了马尔可夫链中值预测方法和马尔可夫链水平特征值方法。基于这些预测，给出了组合预测模型的思想和步骤。其次，在实证研究的一部分，本文采用马尔可夫链组合预测模型预测中国铁路在中国股市的股价，并获得了组合的预测价值。将预测值与其他单个方法获得的预测值进行比较，组合的预测值更准确，因此得出结论，组合的预测方法优于其他马尔可夫预测方法，并丰富马尔可夫链预测系统的理论，它同样表明预测和马尔可夫链预测方法的组合具有很强的适用性。

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