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Korean exchange rate forecasts using Bayesian variable selection

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  • Young Min Kim
  • Seojin Lee

Abstract

Using Bayesian variable selection, we demonstrate that economic variables forecast Korea-US exchange rates better than random walk or random walk with drift model at a short horizon. It implies that the failure of out-of-sample exchange rate forecasts is due to the uncertainties associated with selecting proper predictors, rather than the lack of relationship between the exchange rate and its theoretical determinants. Our results also suggest that time-variant and asymmetric weights on predictors should be taken into account to understand exchange rates dynamics. (JEL classification: C11, C53, F31)

Suggested Citation

  • Young Min Kim & Seojin Lee, 2022. "Korean exchange rate forecasts using Bayesian variable selection," Asia-Pacific Journal of Accounting & Economics, Taylor & Francis Journals, vol. 29(4), pages 1045-1062, July.
    • Handle: RePEc:taf:raaexx:v:29:y:2022:i:4:p:1045-1062
    DOI: 10.1080/16081625.2019.1653777
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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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