[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/116880.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/116880/1/MPRA_paper_116880.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    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).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hyeongwoo Kim & Jisoo Son, 2023. "Forecasting Net Charge-Off Rates of Large U.S. Bank Holding Companies using Macroeconomic Latent Factors," Auburn Economics Working Paper Series auwp2023-02, Department of Economics, Auburn University.
    2. 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.
    3. 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.
    4. Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
    5. Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: Partial Least Squares Factor Model Approach," Working Papers 2017-14, Economic Research Institute, Bank of Korea.
    6. Martin Feldkircher & Thomas Gruber & Isabella Moder, 2014. "Using a Threshold Approach to Flag Vulnerabilities in CESEE Economies," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 3, pages 8-30.
    7. Catão, Luis A.V. & Milesi-Ferretti, Gian Maria, 2014. "External liabilities and crises," Journal of International Economics, Elsevier, vol. 94(1), pages 18-32.
    8. Ryota Nakatani, 2017. "The Effects of Productivity Shocks, Financial Shocks, and Monetary Policy on Exchange Rates: An Application of the Currency Crisis Model and Implications for Emerging Market Crises," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(11), pages 2545-2561, November.
    9. Christofides, Charis & Eicher, Theo S. & Papageorgiou, Chris, 2016. "Did established Early Warning Signals predict the 2008 crises?," European Economic Review, Elsevier, vol. 81(C), pages 103-114.
    10. Layal MansourIshrakieh & Leila Dagher & Sadika El Hariri, 2020. "A financial stress index for a highly dollarized developing country : The case of Lebanon," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 20(2), pages 43-52.
    11. Ahec Šonje, Amina & Babić, Ante & Mlinarević, Katarina, 2003. "Determinants of currency disturbances in transition economies of Central and Eastern Europe," MPRA Paper 83140, University Library of Munich, Germany, revised Mar 2003.
    12. Mansour-Ichrakieh, Layal & Zeaiter, Hussein, 2019. "The role of geopolitical risks on the Turkish economy opportunity or threat," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    13. Alonso-Alvarez, Irma & Molina, Luis, 2023. "How to foresee crises? A new synthetic index of vulnerabilities for emerging economies," Economic Modelling, Elsevier, vol. 125(C).
    14. Chin-Hong Puah, & Tai-Hock Kuek, & M. Affendy Arip,, 2017. "Assessing Thailand’s financial vulnerability: An early warning approach," Business and Economic Horizons (BEH), Prague Development Center, vol. 13(4), pages 496-505, October.
    15. Mustapha Djennas & Mohamed Benbouziane & Meriem Djennas, 2011. "An Approach of Combining Empirical Mode Decomposition and Neural Network Learning for Currency Crisis Forecasting," Working Papers 627, Economic Research Forum, revised 09 Jan 2011.
    16. Yanping Zhao & Jakob Haan & Bert Scholtens & Haizhen Yang, 2014. "Leading Indicators of Currency Crises: Are They the Same in Different Exchange Rate Regimes?," Open Economies Review, Springer, vol. 25(5), pages 937-957, November.
    17. Irma Alonso & Luis Molina, 2019. "The SHERLOC: an EWS-based index of vulnerability for emerging economies," Working Papers 1946, Banco de España.
    18. Tai-Hock Kuek & Chin-Hong Puah & M. Affendy Arip, 2019. "Predicting Financial Vulnerability in Malaysia: Evidence From the Signals Approach," Research in World Economy, Research in World Economy, Sciedu Press, vol. 10(3), pages 89-98, December.
    19. Mansour Ishrakieh, Layal & Dagher, Leila & El Hariri, Sadika, 2018. "The Institute of Financial Economics Financial Stress Index (IFEFSI) for Lebanon," MPRA Paper 116054, University Library of Munich, Germany.
    20. Mpho Bosupeng, 2018. "Leading Indicators and Financial Crisis: A Multi-Sectoral Approach Using Signal Extraction," Journal of Empirical Studies, Conscientia Beam, vol. 5(1), pages 20-44.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:116880. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.