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首页> 外文期刊>Mathematical Problems in Engineering >Forecasting RMB Exchange Rate Based on a Nonlinear Combination Model of ARFIMA, SVM, and BPNN
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Forecasting RMB Exchange Rate Based on a Nonlinear Combination Model of ARFIMA, SVM, and BPNN

机译：基于ARFIMA，SVM和BPNN的非线性组合模型的人民币汇率预测

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摘要

There are various models to predict financial time series like the RMB exchange rate. In this paper, considering the complex characteristics of RMB exchange rate, we build a nonlinear combination model of the autoregressive fractionally integrated moving average (ARFIMA) model, the support vector machine (SVM) model, and the back-propagation neural network (BPNN) model to forecast the RMB exchange rate. The basic idea of the nonlinear combination model (NCM) is to make the prediction more effective by combining different models' advantages, and the weight of the combination model is determined by a nonlinear weighted mechanism. The RMB exchange rate against US dollar (RMB/USD) and the RMB exchange rate against Euro (RMB/EUR) are used as the empirical examples to evaluate the performance of NCM. The results show that the prediction performance of the nonlinear combination model is better than the single models and the linear combination models, and the nonlinear combination model is suitable for the prediction of the special time series, such as the RMB exchange rate.
机译：有多种模型可以预测金融时间序列，例如人民币汇率。在本文中，考虑到人民币汇率的复杂特性，我们建立了自回归分数积分移动平均模型（ARFIMA），支持向量机（SVM）模型和反向传播神经网络（BPNN）的非线性组合模型。模型来预测人民币汇率。非线性组合模型（NCM）的基本思想是通过组合不同模型的优点来使预测更有效，并且组合模型的权重由非线性加权机制确定。人民币兑美元汇率（RMB / USD）和人民币兑欧元汇率（RMB / EUR）被用作评估NCM绩效的经验例子。结果表明，非线性组合模型的预测性能优于单一模型和线性组合模型，并且非线性组合模型适用于人民币汇率等特殊时间序列的预测。

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  • 来源
    《Mathematical Problems in Engineering》 |2015年第12期|635345.1-635345.10|共10页
  • 作者

    Xie Chi; Mao Zhou; Wang Gang-Jin;

  • 作者单位

    Hunan Univ, Coll Business Adm, Changsha 410082, Hunan, Peoples R China|Hunan Univ, Ctr Finance & Investment Management, Changsha 410082, Hunan, Peoples R China;

    Hunan Univ, Coll Business Adm, Changsha 410082, Hunan, Peoples R China;

    Hunan Univ, Coll Business Adm, Changsha 410082, Hunan, Peoples R China|Hunan Univ, Ctr Finance & Investment Management, Changsha 410082, Hunan, Peoples R China;

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