Forgotten effects and heavy moving averages in exchange rate forecasting

Ezequiel Avilés-Ochoa, Ernesto León-Castro, J. M. Lindahl, A. M. G. Lafuente
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引用次数: 13

Abstract

This paper presents the results of using experton, forgotten effects and heavy moving averages operators in three traditional models based purchasing power parity (PPP) model to forecast exchange rate. Therefore, the use of these methods is to improve the forecast error under scenarios of volatility and uncertainty, such as the financial markets and more precise in exchange rate. The heavy ordered weighted moving average weighted average (HOWMAWA) operator is introduced. This new operator includes the weighted average in the usual heavy ordered weighted moving average (HOWMA) operator, considering a degree of importance for each concept that includes the operator. The use of experton and forgotten effects methodology represents the information of the experts in the field and with that information were obtained hidden variables or second degree relations. The results show that the inclusion of the forgotten effects and heavy moving average operators improve our results and reduce the forecast error.
汇率预测中的遗忘效应和重移动平均线
本文介绍了在基于购买力平价(PPP)模型的三种传统模型中使用专家效应、遗忘效应和重移动平均算子进行汇率预测的结果。因此,使用这些方法是为了改善波动和不确定情景下的预测误差,如金融市场和更精确的汇率。引入了重序加权移动平均(HOWMAWA)算子。这个新的运算符在通常的重排序加权移动平均(HOWMA)运算符中包含加权平均,考虑到包含运算符的每个概念的重要性程度。使用专家和遗忘效应方法表示该领域专家的信息,并利用这些信息获得隐变量或二阶关系。结果表明,引入遗忘效应和重移动平均算子改善了预测结果,降低了预测误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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