Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis

Ibrahim Jamali and Ehab Yamani

Journal of International Financial Markets, Institutions and Money, 2019, vol. 61, issue C, 241-263

Abstract: We provide an in-depth analysis of the predictive ability of models with fundamentals and technical indicators for fourteen emerging market currencies. Our findings suggest that the forecasts from the symmetric Taylor rule as well as from a predictive regression exploiting the informational content of the momentum indicator are statistically superior to those of the random walk and other competing models. We combine the forecasts from the two best performing models via simple techniques and assess the economic significance of the out-of-sample forecasts using a trading strategy based on the sign of the predicted currency returns. Our economic significance results demonstrate that the symmetric Taylor rule, momentum and combination forecasts generate the largest net-of-transactions costs and risk-adjusted returns.

Keywords: Exchange rate predictability; Forecasting; Fundamentals; Technical trading; Emerging markets currencies; Currency returns; Trading strategy; Portfolios (search for similar items in EconPapers)
JEL-codes: F31 G14 G15 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1042443119300010
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:intfin:v:61:y:2019:i:c:p:241-263

DOI: 10.1016/j.intfin.2019.04.002

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
Bibliographic data for series maintained by Catherine Liu ().