Forecasting Exchange Rate Volatility with Linear MA Model and Nonlinear GABP Neural Network

摘要：

In order to research RMB exchange rate volatility under exchange rate elastification, this article selects the structure variables about RMB exchange rate volatility to forecast exchange rate volatility by linear moving average model (MA), general back propagation (BP) network and genetic algorithm back propagation (GABP) neural network model respectively. By comparison, we find that, in the lack of flexibility period, month-by-month MA model performs the optimal fitting and forecasting efficiency; along with the exchange rate elastification and liberalization, GABP network model done it best both in volatility value and volatility trend. Exchange rate elastification can deepen the equilibrium relationship between exchange rate and its structure variables; meanwhile, for nonlinear currency fluctuations, nonlinear GABP model could be better choice.

关键词： Exchange Rate Volatility Forecasting Neural Network

作者: Zhigang Huang Guozhong Zheng Yaqin Jia

作者单位: School of Management Fuzhou University, Fujian Fuzhou, 350002, China

会议类型: 国际会议

会议名称: 2011 Fourth International Conference on Business Intelligence and Financial Engineering(第四届商务智能与金融工程国际会议 BIFE2011)

会议地点: 武汉

会议语种:英文

页码: 22-26

在线出版日期: 2011-10-17（万方平台首次上网日期，不代表论文的发表时间）