Artikel
Predicting currency crises: A novel approach combining random forests and wavelet transform
We propose a novel approach that combines random forests and the wavelet transform to model the prediction of currency crises. Our classification model of random forests, built using both standard predictors and wavelet predictors, and obtained from the wavelet transform, achieves a demonstrably high level of predictive accuracy. We also use variable importance measures to find that wavelet predictors are key predictors of crises. In particular, we find that real exchange rate appreciation and overvaluation, which are measured over a horizon of 16-32 months, are the most important.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 11 ; Year: 2018 ; Issue: 4 ; Pages: 1-11 ; Basel: MDPI
- Klassifikation
-
Wirtschaft
Foreign Exchange
International Finance Forecasting and Simulation: Models and Applications
Macroeconomic Aspects of International Trade and Finance: Forecasting and Simulation: Models and Applications
- Thema
-
currency crisis
random forests
wavelet transform
predictive accuracy
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Xu, Lei
Kinkyo, Takuji
Hamori, Shigeyuki
- Ereignis
-
Veröffentlichung
- (wer)
-
MDPI
- (wo)
-
Basel
- (wann)
-
2018
- DOI
-
doi:10.3390/jrfm11040086
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Xu, Lei
- Kinkyo, Takuji
- Hamori, Shigeyuki
- MDPI
Entstanden
- 2018
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