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Conditional Predictive Ability of Exchange Rates in Long Run Regressions

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  • Pablo Pincheira

    (Central Bank of Chile)

Abstract

In this paper we evaluate exchange rate predictability using a framework developed by Giacomini and White (2006). This new framework tests for conditional predictive ability rather than unconditional predictive ability, which has been the standard approach. Using several shrinkage based forecasting methods, including new methods proposed here, we evaluate conditional predictability of five bilateral exchange rates at differing horizons. Our results indicate that for most currencies a random walk would not be the optimal forecasting method in a real time forecasting exercise, at least for some predictive horizons. We also show that our proposed shrinkage methods in general perform on par with Bayesian shrinkage and ridge regressions, and sometimes they even perform better.

Suggested Citation

  • Pablo Pincheira, 2013. "Conditional Predictive Ability of Exchange Rates in Long Run Regressions," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 28(2), pages 3-35, October.
    • Handle: RePEc:ila:anaeco:v:28:y:2013:i:2:p:3-35
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    More about this item

    Keywords

    Exchange rate predictability; conditional predictive ability; Bayesian shrinkage; ridge regression; forecast evaluation;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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