Michele Ca' Zorzi, Marcin Kolasa, Michał Rubaszek, 03 March 2017

Macroeconomic models have been criticised for their inability to forecast exchange rates better than the random walk model. This column argues that open-economy DGSE models are useful in forecasting the real exchange rate but not the nominal exchange rate, owing to their failure to capture adequately the international co-movement of prices. They correctly predict, however, that the bulk of the real exchange rate adjustment occurs through the nominal rate. The central role of the nominal rate in restoring price competitiveness in flexible exchange rate regimes can be exploited from a forecasting perspective. 

Michele Ca' Zorzi, Jakub Mućk, Michał Rubaszek, 13 February 2015

Notwithstanding the progress made in the field of exchange rate economics, we still know very little of what drives major currencies. This column argues that the best that one can do is to assume that currencies move to gradually restore (relative) purchasing power parity. Contrary to widely held beliefs, this is in general a much better strategy than to just assume that the exchange rate behaves like a random walk. 

Barbara Rossi, 14 November 2013

Predicting exchange rates is still an inexact science. Economic models perform poorly, and a plethora of alternative methods have been attempted. This column guides the reader through the state of the art, reviewing various predictors, models, and data specifications. Despite a large and divergent literature chasing this holy grail, the toughest benchmark remains the random walk without drift.

Pasquale Della Corte, Lucio Sarno, Ilias Tsiakas, 18 January 2008

The forward premium, the difference between the forward exchange rate and the spot exchange rate, contains economically valuable information about the future of exchange rates. Here is the evidence that it can help predict short-run rates and that investors who ignore it and use random walk models may be leaving money on the table.

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