Exchange rate forecasting using economic models and technical trading rules

Nima Zarrabi, Stuart Snaith and Jerry Coakley

The European Journal of Finance, 2022, vol. 28, issue 10, 997-1018

Abstract: The use of technical analysis by practitioners in the foreign exchange market contrasts with the ongoing debate among academics on the poor predictive ability of macroeconomic variables. This paper compares these two methods by constructing pools of economic models and technical trading rules and evaluates their in-sample and out-of-sample performance both locally and globally. Results suggest the presence of local forecastability that is overlooked when relying on global measures of predictability. The local predictability is captured using a rolling model selection approach to generate aggregate forecasts across separate pools of economic models and technical trading rules as well as both combined. The out-of-sample results for our aggregate forecasts using pools of economic models fail to beat the random walk as do pools of technical trading models. However combining the two pools of models results in forecasts that beat the random walk for four out of the six sample currencies. This result suggests that exchange rate forecasts can be improved by pooling both sets of models.

Date: 2022
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DOI: 10.1080/1351847X.2021.1949368

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