Out-of-sample forecasting of foreign exchange rates: The band spectral regression and LASSO

Tatsuma Wada

Journal of International Money and Finance, 2022, vol. 128, issue C

Abstract: We propose to utilize the band spectral regression for out-of-sample forecasts of exchange rates. When one period ahead forecast is considered, there is some evidence that the band spectral regression improves its accuracy, especially when the Taylor rule fundamentals model is employed. However, when the forecasting horizon increases, the purchasing power parity (PPP) fundamentals model is found to be powerful, and we can improve the out-of-sample forecast by selecting appropriate frequency bands. Bayesian model averaging shows that placing a large weight on the business cycle frequency improves the accuracy of the out-of-sample forecasting of the PPP model (as well as the monetary fundamentals model) when a longer forecasting horizon is our focus. Without specifying the frequency bands prior to applying the regression, LASSO can provide better out-of-sample exchange rate forecasts for many cases – most patently for the PPP fundamentals model – and provide information about the dynamic relationship between forecasting variables and exchange rates. The frequency domain approach not only improves the accuracy of exchange rate forecast but provides insights for understanding why the PPP fundamentals act as a powerful predictor when the forecasting horizon increases and there is a possible improvement in the time domain regression forecast.

Keywords: Band Spectral Regression; Bayesian Model Averaging; Exchange Rate Models; Frequency Domain; LASSO (search for similar items in EconPapers)
JEL-codes: C22 C52 F31 F47 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S026156062200122X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jimfin:v:128:y:2022:i:c:s026156062200122x

DOI: 10.1016/j.jimonfin.2022.102719

Access Statistics for this article

Journal of International Money and Finance is currently edited by J. R. Lothian

More articles in Journal of International Money and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().