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FX forecasting using B-WEMA: Variant of Brown's Double Exponential Smoothing

机译:使用B-WEMA的外汇预测:布朗双指数平滑法的变体

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A new variant of B-DES (Brown's Double Exponential Smoothing), as a type of classical MA (Moving Averages) method commonly used in time series data forecasting, had been introduced and known as B-WEMA. It has proven to have a better accuracy and robustness level compare to the other moving average methods, such as WMA and B-DES. However, B-WEMA implementation on a real financial time series data such as foreign exchange (FX) had never been done. Therefore, in this research we try to implement B-WEMA as a variant of MA method on FX forecasting and compare the results with other moving average methods using the MSE and MAPE forecast error measurements criteria. Results from the experiments conducted show that B-WEMA has a better accuracy level compared to WMA and B-DES methods.
机译:作为时间序列数据预测中常用的经典MA(移动平均值)方法的一种,B-DES(布朗双指数平滑)的一种新变体已被引入,并被称为B-WEMA。与WMA和B-DES等其他移动平均方法相比,它具有更高的准确性和鲁棒性。但是,从未完成对真实财务时间序列数据(例如外汇(FX))的B-WEMA实施。因此,在这项研究中,我们尝试将B-WEMA作为FX预测中MA方法的一种实现方式,并使用MSE和MAPE预测误差测量标准将结果与其他移动平均方法进行比较。实验结果表明,与WMA和B-DES方法相比,B-WEMA的准确性更高。

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