A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Recession forecasting with high-dimensional data
Tekijät: Nevasalmi Lauri
Kustantaja: WILEY
Julkaisuvuosi: 2022
Journal: Journal of Forecasting
Tietokannassa oleva lehden nimi: JOURNAL OF FORECASTING
Lehden akronyymi: J FORECASTING
Sivujen määrä: 13
ISSN: 0277-6693
eISSN: 1099-131X
DOI: https://doi.org/10.1002/for.2823
Verkko-osoite: https://doi.org/10.1002/for.2823
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/67835244
Tiivistelmä
In this paper, a large amount of different financial and macroeconomic variables are used to predict the U.S. recession periods. We propose a new cost-sensitive extension to the gradient boosting model, which can take into account the class imbalance problem of the binary response variable. The class imbalance, caused by the scarcity of recession periods in our application, is a problem that is emphasized with high-dimensional datasets. Our empirical results show that the introduced cost-sensitive extension outperforms the traditional gradient boosting model in both in-sample and out-of-sample forecasting. Among the large set of candidate predictors, different types of interest rate spreads turn out to be the most important predictors when forecasting U.S. recession periods.
In this paper, a large amount of different financial and macroeconomic variables are used to predict the U.S. recession periods. We propose a new cost-sensitive extension to the gradient boosting model, which can take into account the class imbalance problem of the binary response variable. The class imbalance, caused by the scarcity of recession periods in our application, is a problem that is emphasized with high-dimensional datasets. Our empirical results show that the introduced cost-sensitive extension outperforms the traditional gradient boosting model in both in-sample and out-of-sample forecasting. Among the large set of candidate predictors, different types of interest rate spreads turn out to be the most important predictors when forecasting U.S. recession periods.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
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