Time-Varying Parameters and the Out-of-Sample Forecasting Performance of Structural Exchange Rate Models

1987 ◽  
Vol 5 (1) ◽  
pp. 87 ◽  
Author(s):  
Christian C. P. Wolff
Keyword(s):  
Exchange Rate ◽  
Time Varying ◽  
Varying Parameters ◽  
Forecasting Performance ◽  
Time Varying Parameters ◽  
Out Of Sample ◽  
Exchange Rate Models ◽  
Structural Exchange Rate Models

scholarly journals Model Uncertainty and Exchange Rate Forecasting

2017 ◽  
Vol 52 (1) ◽  
pp. 341-363 ◽  
Author(s):  
Roy Kouwenberg ◽  
Agnieszka Markiewicz ◽  
Ralph Verhoeks ◽  
Remco C. J. Zwinkels
Keyword(s):  
Exchange Rate ◽  
Model Selection ◽  
Model Uncertainty ◽  
Selection Rule ◽  
Time Varying ◽  
Exchange Rate Forecasting ◽  
Out Of Sample ◽  
Small Set ◽  
Strong Performance ◽  
Exchange Rate Models

Exchange rate models with uncertain and incomplete information predict that investors focus on a small set of fundamentals that changes frequently over time. We design a model selection rule that captures the current set of fundamentals that best predicts the exchange rate. Out-of-sample tests show that the forecasts made by this rule significantly beat a random walk for 5 out of 10 currencies. Furthermore, the currency forecasts generate meaningful investment profits. We demonstrate that the strong performance of the model selection rule is driven by time-varying weights attached to a small set of fundamentals, in line with theory.

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