Comparing Forecast Performance of Exchange Rate Models

Lillie Lam, Laurence Fung and Ip-wing Yu
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Lillie Lam: Research Department, Hong Kong Monetary Authority
Laurence Fung: Research Department, Hong Kong Monetary Authority
Ip-wing Yu: Research Department, Hong Kong Monetary Authority

No 808, Working Papers from Hong Kong Monetary Authority

Abstract: Exchange-rate movement is regularly monitored by central banks for macroeconomic-analysis and market-surveillance purposes. Notwithstanding the pioneering study of Meese and Rogoff (1983), which shows the superiority of the random-walk model in out-of-sample exchange-rate forecast, there is some evidence that exchange-rate movement may be predictable at longer time horizons. This study compares the forecast performance of the Purchasing Power Parity model, Uncovered Interest Rate Parity model, Sticky Price Monetary model, the model based on the Bayesian Model Averaging technique, and a combined forecast of all the above models with benchmarks given by the random-walk model and the historical average return. Empirical results suggest that the combined forecast outperforms the benchmarks and generally yields better results than relying on a single model.

Keywords: Bayesian Analysis; Model Evaluation and Selection; Forecasting and Other Model Application (search for similar items in EconPapers)
JEL-codes: C11 C52 C53 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2008-06
New Economics Papers: this item is included in nep-cba and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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