汇率预报的非线性组合建模与预测方法研究

Research on Nonlinear Combining Modeling and Forecasting of Foreign Exchange Rate

近年来的经济统计研究表明,组合预测比单项预测具有更高的预测精度,但线性组合预测方法在汇率的组合建模与预测方面存着较大的局限性。本文提出了一种基于支持向量机回归(SVM)的汇率非线性组合建模与预测新方法,并讨论了建模中SVM核函数、损失函数的选取和容量控制等问题。对于英镑、法郎、瑞士法郎、日元对美元等汇率时间序列的组合建模与预测结果表明,该方法具有很强的学习与泛化能力,在处理外汇市场这种具有一定程度不确定性的非线性系统的组合建模与预测方面有很好的应用价值。

It has been shown in recent economic and statistical studies that combining forecasts may produce more accurate forecasts than individual ones.However,the linear combination forecasting method is known to have the limitation for composite modeling and forecasting of foreign exchange rates.This paper presents a new nonlinear composite forecasting method for exchange rate modeling and forecasting based on support vector machines regression.Furthermore,the problems how to select the kernel function,loss function and control capacity,and so on,are discussed with simulation demonstration.It has been shown by the composite modeling and forecasting results about the exchange rate time series of the British pound,the French franc,the Swiss franc and the Japanese yen against U.S.dollar that the method has reinforcement learning properties and mapping capabilities.With respect to composite modeling and forecasting of nonlinear system which has some uncertainties,the method is applicable. 