基于Markov链的华夏银行股票波动短期预测

Short-Term Forecast of Huaxia Bank Stock Volatility Based on Markov Chain

随着社会经济的发展,人们逐渐建立了投资理财的意识,其中股票就是常见的投资对象。如果提供具有参考依据的股票预测结果,对广大投资者以及企业自身而言都将得到可观的收益。本文将Markov链作为预测股票的方法,简要阐述Markov链及其相关的基础理论,以华夏银行作为实证,检验Markov链预测股票涨幅的效果。本文收集和整理了95个交易日的股票数据,以每日涨幅作为依据,划分成为下跌、略微下跌、略微上升和上升共四个状态,计算各阶转移概率矩阵,并在预测前对数据进行了马氏性检验。通过对比发现之后六个交易日中,大部分实际涨幅情况落在预测区间内,并简要分析了华夏银行股票当前走势的可能原因。得出Markov链对股票预测准确度较好的结论,分析出状态转移矩阵的改变是Markov链在中长期预测精准度下降的原因。

With the development of social economy, people have gradually established the awareness of in-vestment and financial management, among which stocks are the common investment object. If the stock forecast results with reference basis are provided, both the majority of investors and the enterprise itself will get considerable returns. In this paper, Markov chain is used as the method to predict stocks, Markov chain and its related basic theories were briefly expounded, taking Huaxia Bank as the empirical to test the effect of Markov chain in predicting stock increase. This paper collects and arranges the stock data of 95 trading days, based on the daily increase, divided into four states: fall, slightly fall, slightly rise and rise, and calculates the transition probability matrix of each order, and conducts the Markov property on the data before the prediction. Through com-parison, in the following six trading days, most of the actual gains fell within the forecast range, and the possible reasons for the current trend of Huaxia Bank stock were briefly analyzed. The conclusion is drawn that the Markov chain has good accuracy in stock prediction, and the change of the state transition matrix is the reason for the decrease in the prediction accuracy of the Markov chain in the medium and long term.