基于机器学习的股指预测算法

发布时间：2018-01-01 21:52

本文关键词：基于机器学习的股指预测算法　出处：《天津工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：股票价格指数的变化可以有效反映股票市场各种股票的价格水平,帮助投资者理解股票变动情况。当下,中国股票市场在国民经济中的作用和地位是越来越重要。因此,研究股指变化规律对于市场管理者和广大投资者来说都具有很重要的意义。本文通过建立回归模型来预测股指的变化规律。首先,从实验数据的选取入手。不同于以往的研究方法,本文采用多种实验数据,主要包括大盘指数和股票历史交易数据。由于股指是通过股票价格加权求得,通过股票的交易数据可以更有效的求得股指的变化规律。其次,本文提出多种新的特征向量用于股票指数的预测。特征向量是预测模型重要的组成部分,本文从不同的方面求得多个特征向量,包括:成交分布、成交对比、上升下降趋势总对比、上升下降功能、动能趋势等。最后,本文选择支持向量回归作为我们的预测模型,并使用遗传算法寻求模型的最优参数。通过大量真实的股票数据验证了本文得出的模型可以有效的对股指的变化进行预测,帮助广大投资者了解股票市场的变化情况,对于普通投资者的股票投资有一定的参考意义。
[Abstract]:The change of the stock price index can effectively reflect the stock market all the stock price level, to help investors understand the stock changes. At the moment, and the status of China stock market in the national economy is more and more important. Therefore, the change law of stock market for managers and investors have a very important significance. This paper establish the regression model to predict the changes of stock index. First of all, starting from the selected experimental data. Different from the previous research methods, by using various experimental data, including the stock market index and historical transaction data. Because the stock index is obtained through the weighted stock price, the stock transaction data through the changes of the index can be obtained more effectively. Secondly, this paper presents a variety of new feature vector is used to predict the stock index. The feature vector is an important prediction model Part of this paper, from different aspects of the multiple feature vectors, including: transaction distribution, turnover increased contrast, downward trend in total contrast, the rise and fall of function, kinetic energy trend. Finally, this paper choose support vector regression as our prediction model, and use the genetic algorithm to seek the optimal parameters of the model. Through a large number of real the stock data to verify the model can effectively predict the change of stock index, help investors understand the change of the stock market, it has certain reference significance for ordinary investors in the stock investment.

【学位授予单位】：天津工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F832.51;TP181

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