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Forecasting exchange rates for Central and Eastern European currencies using country-specific factors
Journal of Forecasting ( IF 3.4 ) Pub Date : 2020-12-16 , DOI: 10.1002/for.2749
Krystian Jaworski 1
Affiliation  

This study builds on two strands of the literature regarding exchange rates—developing methods to forecast them and attempting to find a link between exchange rates and macroeconomic fundamentals (i.e., addressing so called “exchange rate disconnect puzzle”). We propose looking separately at its global component (common for all the currencies) and the local component (country-specific one) instead of modeling and forecasting the exchange rate directly. We demonstrate that in the last few years, local factors have been gaining importance in shaping the exchange rate returns for the Polish Zloty, Hungarian Forint, Czech Koruna, and Romanian Leu. We further show that the main drivers of the local component of exchange rate returns are the future values of the gross domestic product growth rate and consumer price index inflation. Using principal component analysis combined with linear regression, we exploit this tendency for forecasting purposes. Our novel approach yields superior results compared to the random walk in out-of-sample forecasting exercise at horizons of 1 month to over a year in the case of Central and Eastern European currencies. The results withstand the sensitivity and robustness analysis.

中文翻译:

使用特定国家因素预测中欧和东欧货币的汇率

本研究建立在有关汇率的两方面文献的基础上——开发预测汇率的方法并试图找到汇率与宏观经济基本面之间的联系(即解决所谓的“汇率脱节难题”)。我们建议分别查看其全球部分(所有货币通用)和本地部分(特定国家的部分),而不是直接对汇率进行建模和预测。我们证明,在过去几年中,本地因素在塑造波兰兹罗提、匈牙利福林、捷克克朗和罗马尼亚列伊的汇率回报方面变得越来越重要。我们进一步表明,汇率回报本地成分的主要驱动因素是国内生产总值增长率和消费者价格指数通胀的未来价值。使用主成分分析结合线性回归,我们利用这种趋势进行预测。与中欧和东欧货币在 1 个月到一年多的范围内的样本外预测练习中的随机游走相比,我们的新方法产生了更好的结果。结果经得起敏感性和稳健性分析。
更新日期:2020-12-16
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