A wavelet neural network application to predict financial market crises

摘要：

Forecasting currency crisis is an important financial problem that has received much attention especially because of its intrinsic difficulty and practical applications. Some non-parameter models,such as KLRs single analysis method,have been proposed for obtaining accurate prediction results,in an attempt to remedy the performance of parameter models,such as Probit/Logit method. This paper develops a new approach for predicting currency crisis,namely Wavelet Neural Networks (WNN) model. Using same indicators and a set of data,we analyze the probability of crisis by this approach. According to result,both models are able to signal currency crises reasonably well in-sample,and that the forecasting power of WNN out-of-sample has better performance than ANN.

关键词： wavelet neural network forecasting currency crisis

作者: Yin Yu

作者单位: School of Management,Donghua University,China

会议类型: 国际会议

会议名称: The First International Conference on Management Innovation(ICMI 2007)(管理创新会议)

会议地点: 上海

会议语种:英文

页码: 519-523

在线出版日期: 2007-06-04（万方平台首次上网日期，不代表论文的发表时间）