外汇汇率预测的一种前馈神经网络方法及其应用

A Feedforward Neural Network Method for Forecasting Foreign Exchange Rates and Its Application

目前外汇交易量逐渐扩大,外汇交易市场在各国交易市场中具有极其重要的地位,其中影响外汇交易市场的关键因素是外汇汇率。随着人工智能的发展,人工神经网络将广泛应用于生活中。本文利用前馈神经网络建立模型预测汇率的收盘价,将外汇汇率收盘价的历史数据集作为一组时间序列,利用前馈神经网络构建理论模型,通过构造的理论模型来预测外汇汇率的收盘价。本文使用美元兑人民币、美元兑欧元、美元兑英镑、美元兑瑞郎四种汇率收盘价数据,实证结果表明该模型具有良好的预测精度,并对此模型的优缺点进行了讨论,期望能为外汇投资提供建议。

At present, the foreign exchange transaction volume expands gradually;the foreign exchange transaction market has the extremely important position in each market. Among them, the key factor that affects foreign exchange market is foreign exchange rate. Along with the development of artificial intelligence, artificial neural network will be widely used in life. In this paper, a Feedforward neural network is used to establish a model to predict the closing price of exchange rates, and the historical data set of closing prices of foreign exchange rates is used as a set of time series, then using the theory of Feedforword neural network to build model. At last, by constructing the theoretical model to predict the closing price of foreign exchange rate. This article uses data on the closing prices of four exchange rates: USD to RMB, USD to Euro, USD to GBP, USD to Swiss Franc, the empirical results show that the model is of high prediction accuracy, and the advantages and disadvantages of this model are discussed in order to provide suggestions for foreign exchange investment.