基于变维分形的股票指数预测模型

为了解决投资者提出的希望能够寻找一种易于实现的预测方法来提高股票指数短期预测精度的问题,采用变维分形、累计和变换对数据进行分析,预测时对上证指数的原始数据进行一系列变换以及分析后,从中选择一种能够与模型符合良好的最优变换来确定相应的分形参数,即能用分形分布处理变换后的数据。给出了用分形方法对上证指数进行短期预测的实例并结合数值模拟图形进行比较分析,经研究得出基于分形维的预测方法对于股票指数的短期预测精度较高,并且对短期预测具有很好的研究价值和广阔的应用前景。

A forecast model of stock index based on variable dimension fractal

In order to find an easy way to improve the accuracy of short-term stock index forecast,this paper proposes a new data analysis method by applying variable dimension fractal,accumulation and transformation methods.Using the raw data from Shanghai Stock Exchange,a series of transformations on the raw data are performed and a best transformation is selected based on the optimal fitness to the model.The best transformation is then used to determine the corresponding fractal parameters.Subsequently,the fractal ...