Predictive content of equilibrium exchange rate models

Understanding the relationship between macroeconomic fundamentals and exchange rates and the ability to predict their future movements are important to many economic agents. For policy-makers, the key issue is that fluctuations in exchange rates exert a large impact on the economy. For this reason, central institutions analyse the dynamics of exchange rates when making decisions on economic policy, as well as when managing their FX assets and liabilities. For investors, an important issue is that foreign assets often constitute a large part of their portfolios.

The ability to predict FX movements can therefore be exploited to construct profitable trading strategies. Ultimately, for exporters and importers, exchange rate fluctuations constitute one of the most important risk factors for their activity.  The reference benchmark in exchange rate forecasting is a simple no-change forecast, assuming that the future price will stay at the current level. It turns out that constructing econometric or economic models that can consistently outperform the no-change forecast is a real challenge.

In the project, we will address this issue by conducting a comprehensive analysis on the predictive content of equilibrium exchange rate (EER) models. The usefulness of EER models, which assume that there is a long-term relationship between exchange rates and macroeconomic fundamentals, will be tested using three approaches. First, we will focus on the accuracy of exchange rate forecasts that are based on EER models. Second, we will evaluate the characteristics of FX trading strategies based on EER models. Third, we will use the cross-sectional perspective to explore if EER misalignments are leading indicators for macroeconomic variables.  The results of the project should help in understanding the relationship between exchange rates and macroeconomic fundamentals, and can thus be used in economic policy making. More importantly, we plan to present methods helpful in exchange rate forecasting, which could contribute to better management of FX risk.

Project director:
Michał Rubaszek, Ph.D., SGH Professor
Financing institution:
National Science Centre
Project duration:
February 2020 - February 2023
Web of science classification category:
Organizational unit (collegium/department/unit):
SGH Warsaw School of Economics » Collegia » Collegium of Economic Analysis