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What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?

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  • Kim, Hyeongwoo
  • Son, Jisoo

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 and real estate loan CORs, while enhancing predictive contents for consumer loan CORs is difficult especially at short horizons. Real activity factors improve the out-of-sample predictability over the benchmarks for business loan CORs even when financial sector factors are excluded.

Suggested Citation

  • Kim, Hyeongwoo & Son, Jisoo, 2023. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," MPRA Paper 116880, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:116880
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    1. Frankel, Jeffrey & Saravelos, George, 2012. "Can leading indicators assess country vulnerability? Evidence from the 2008–09 global financial crisis," Journal of International Economics, Elsevier, vol. 87(2), pages 216-231.
    2. Frankel, Jeffrey A. & Rose, Andrew K., 1996. "Currency Crashes in Emerging Markets: Empirical Indicators," Center for International and Development Economics Research (CIDER) Working Papers 233424, University of California-Berkeley, Department of Economics.
    3. Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
    4. Christensen, Ian & Li, Fuchun, 2014. "Predicting financial stress events: A signal extraction approach," Journal of Financial Stability, Elsevier, vol. 14(C), pages 54-65.
    5. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2023. "Forecasting with a panel Tobit model," Quantitative Economics, Econometric Society, vol. 14(1), pages 117-159, January.
    6. Hyeongwoo Kim & Wen Shi & Hyun Hak Kim, 2020. "Forecasting financial stress indices in Korea: a factor model approach," Empirical Economics, Springer, vol. 59(6), pages 2859-2898, December.
    7. Hali J. Edison, 2003. "Do indicators of financial crises work? An evaluation of an early warning system," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 8(1), pages 11-53.
    8. Mr. Evan C Tanner, 2002. "Exchange Market Pressure, Currency Crises, and Monetary Policy: Additional Evidence From Emerging Markets," IMF Working Papers 2002/014, International Monetary Fund.
    9. Graciela Kaminsky & Saul Lizondo & Carmen M. Reinhart, 1998. "Leading Indicators of Currency Crises," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 1-48, March.
    10. Charles Engel & Nelson C. Mark & Kenneth D. West, 2015. "Factor Model Forecasts of Exchange Rates," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 32-55, February.
    11. Hyeongwoo Kim & Wen Shi, 2021. "Forecasting financial vulnerability in the USA: A factor model approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 439-457, April.
    12. Cipollini, A. & Kapetanios, G., 2009. "Forecasting financial crises and contagion in Asia using dynamic factor analysis," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 188-200, March.
    13. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    14. Yunjung Kim & Cheolbeom Park, 2020. "Are exchange rates disconnected from macroeconomic variables? Evidence from the factor approach," Empirical Economics, Springer, vol. 58(4), pages 1713-1747, April.
    15. Brüggemann, Axel & Linne, Thomas, 1999. "How Good are Leading Indicators for Currency and Banking Crises in Central and Eastern Europe? An Empirical Test," IWH Discussion Papers 95/1999, Halle Institute for Economic Research (IWH).
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    Cited by:

    1. Carlos Canizares Martinez, 2023. "Leaning against housing booms fueled by credit," Working and Discussion Papers WP 9/2023, Research Department, National Bank of Slovakia.

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    More about this item

    Keywords

    Net Charge-Off Rate; Bank Holding Companies; Principal Component Analysis; Partial Least Squares; Out-of-Sample Forecast;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • F3 - International Economics - - International Finance

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