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I build a commodity strategy for exchange rate forecasting that conditions on changes in the global prices of commodity indices. First, I document that commodity prices have significant out-of-sample predictive ability for the future exchange rates of several commodity exporters and importers on the daily frequency. However, unlike the findings of Chen, Rogoff and Rossi (2010), I report that the reverse forecasting regression does not survive out-of-sample testing. Second, I find a significant cross-sectional spread in both spot and excess returns of 6\% p.a. between the currencies that are predicted to appreciate and those that are predicted to depreciate by the commodity strategy. More importantly, the returns appear to be uncorrelated to those of popular exchange rate strategies such as the carry trade and currency momentum. Furthermore, the spread in returns is not explained by traditional risk factors; however, it is partly accounted for by the strategy's high transaction costs. Net profitability can be restored by either implementing a simple market timing rule or by investing in developed markets with low costs and high liquidity.
