 Forecasting exchange rate volatility: An amalgamation approachAntonios K. Alexandridis, Ekaterini Panopoulou and Ioannis Souropanis Journal of International Financial Markets, Institutions and Money, 2024, vol. 97, issue C Abstract: The importance of exchange rate volatility forecasting has both practical and academic merit. Our aim is to provide a comprehensive analysis of the forecasting ability of financial and macroeconomics variables for future exchange rate volatility. We employ seven widely traded currencies against the US dollar and examine linear models and a variety of machine learning, dimensionality reduction and forecast combination approaches, along with creating a grand forecast (amalgamation approach) from these approaches. Our findings highlight the predictive power of the amalgamation approach, as well as the positive contribution of macroeconomic and financial variables in the forecasting experiment. Furthermore, we generate forecasts on the separate frequencies of volatility using wavelet analysis, in order to extract frequency-related information and examine timing effects in the performance of the methods. Keywords: Exchange rates; Volatility forecasting; Forecast combination; Machine learning; Dimensionality reduction; Wavelet decomposition (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:intfin:v:97:y:2024:i:c:s1042443124001331 DOI: 10.1016/j.intfin.2024.102067 Access Statistics for this article Journal of International Financial Markets, Institutions and Money is currently edited by I. Mathur and C. J. Neely More articles in Journal of International Financial Markets, Institutions and Money from Elsevier |
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