摘要
针对汇率变化的非线性特性与线性组合预测方法在解决非平衡时间序列的组合建模问题所遇到的困难和存在的不足,本文建立了汇率的非线性组合预测模型,并确定了有效的学习算法。应用从1985年1月至1992年12月英镑对美元的月末数据,进行了实证研究。结果表明:该方法具有很强的学习与泛化能力,在处理诸如汇率时间序列这种具有一定程度不确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。
Taking aim at the nonlinear nature of the exchange rate data and the problem how to overcome the difficulties and drawbacks in combined modeling non-stationary time series by using linear combination forecasting. A nonlinear combination forecasting model for exchange rate is presented and a effective learning algorithm is also produced. A experiments research on combined modeling and forecasting the exchange rates of the British pound/US dollar over the period from January 1985 to December 1992 monthly show...
出处
《中国管理科学》
CSSCI
2000年第S1期212-218,共7页
Chinese Journal of Management Science
基金
国家自然科学基金资助项目!(79770105)
重庆市科委重点软科学资助项目!(5569)
关键词
汇率
组合预测
模糊逻辑系统
遗传算法
Exchange rates
Combining forecasts
Fuzzy logic system
Genetic algorithm