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A bi-annual forecasting model of currency crises

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  • Takuji Kinkyo

Abstract

This study proposes a novel approach that combines random forests and discrete wavelet transform (DWT) to construct a bi-annual forecasting model of currency crises. The proposed model can achieve a reasonably high level of accuracy in predicting crises and demonstrates that the DWT of monthly real exchange rates and foreign reserves can serve as reliable predictors. The predicted probability of crises in individual countries is visualized through a map, which indicates that the risk of crises has increased substantially across regions in the second half of 2018.

Suggested Citation

  • Takuji Kinkyo, 2020. "A bi-annual forecasting model of currency crises," Applied Economics Letters, Taylor & Francis Journals, vol. 27(4), pages 255-261, February.
    • Handle: RePEc:taf:apeclt:v:27:y:2020:i:4:p:255-261
    DOI: 10.1080/13504851.2019.1613492
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    Cited by:

    1. Kinkyo, Takuji, 2020. "Volatility interdependence on foreign exchange markets: The contribution of cross-rates," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    2. Chen, Jianyu & Zhang, Jianshun, 2023. "Crude oil price shocks, volatility spillovers, and global systemic financial risk transmission mechanisms: Evidence from the stock and foreign exchange markets," Resources Policy, Elsevier, vol. 85(PB).

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