Predicting Returns of Exchange Rate from Oil Prices: Machine Learning Approach

B. T. Khoa, T. Huynh, Nguyen Thi Diem Huong
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Abstract

Using data collected monthly beginning in January 2010 and ending in December 2022, this research intends to forecast the returns of the Vietnam Dong/US Dollar Exchange Rate on the oil price worldwide. Following the current literature, this investigation develops a predictive model that considers the most important aspects of the predictor and the predicted series. Oil and the returns on the exchange rate were shown to have a linearly negative connection. Both net oil exporters and net oil importers might anticipate favorable exchange rate returns if oil prices remain stable. Finally, we evaluate how different forecasting methods perform in and out of the sample. While there was higher volatility in the out-of-sample period, the research indicated that the prediction error was still small.
从油价预测汇率收益:机器学习方法
使用从2010年1月开始到2022年12月结束的每月收集的数据,本研究旨在预测越南盾/美元汇率对全球油价的回报。根据目前的文献,本研究开发了一个预测模型,该模型考虑了预测器和预测序列的最重要方面。结果表明,石油和汇率回报率呈线性负相关。如果油价保持稳定,石油净出口国和石油净进口国都可能预期有利的汇率回报。最后,我们评估了不同的预测方法在样本内外的表现。虽然样本外期波动较大,但研究表明,预测误差仍然很小。
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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