Forecasting Net Charge-Off Rates of Large U.S. Bank Holding Companies using Macroeconomic Latent Factors

No auwp2023-02, Auburn Economics Working Paper Series from Department of Economics, Auburn University

Abstract: Charge-offs signal important information about the riskiness of loan portfolios in the banking system, which can generate systemic risk towards deep recessions. We compiled the net charge-off rate (COR) data of the top 10 bank holding companies (BHCs) in the U.S., utilizing consolidated financial statements. We propose factor-augmented forecasting models for CORs by estimating latent common factors, including targeted factors, via an array of data dimensionality reduction methods for a large panel of macroeconomic predictors. Our models outperform the benchmark models especially well for business loan CORs, while enhancing predictive contents for consumer loans are harder at short horizons. Real activity factors enhance the out-of-sample predictability for business loan CORs even when financial sector factors are excluded.

Keywords: Net Charge-Off Rate; Bank Holding Companies; Principal Component Analysis; Partial Least Squares; Out-of-Sample Forecast (search for similar items in EconPapers)
JEL-codes: C38 C53 C55 G01 G17 (search for similar items in EconPapers)
Date: 2023-02
New Economics Papers: this item is included in nep-ban, nep-fdg and nep-for
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