The performance of alternative VAR models in forecasting exchange rates

Te Ru Liu, Mary E. Gerlow, Scott H. Irwin

Research output: Contribution to journalArticlepeer-review


The purpose of this research is to analyze the forecasting accuracy of full vector autoregressive (FVAR), mixed vector autoregressive (MVAR), and Bayesian vector autoregressive (BVAR) models of the US dollar/yen, US dollar/Canadian dollar, and US dollar/Deutsche mark exchange rates. The VAR specifications are based on a monetary/asset model of exchange rate determination. Out-of-sample results (1983:1-1989:12) indicate that the forecasting performance of restricted VARs (MVARs and BVARs) is substantially better than that of unrestricted VARs (FVARs). Overall, the results show that a monetary/asset model in a VAR representation does have forecasting value for some exchange rates.

Original languageEnglish (US)
Pages (from-to)419-433
Number of pages15
JournalInternational Journal of Forecasting
Issue number3
StatePublished - Nov 1994
Externally publishedYes


  • Exchange rates
  • Forecasting
  • Vector autoregression

ASJC Scopus subject areas

  • Business and International Management

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