IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v178y2019icp95-97.html

Forecasting credit losses with the reversal in credit spreads

Author

Listed:
  • Du, Ding

Abstract

López-Salido et al. (2017) find that there is predictable reversal in credit spreads. Because in theory credit spreads reflect expected future credit losses, we explore if the predictable reversal in credit spreads helps forecast loan charge-offs, particularly for big banks. Empirically, we find robust supporting evidence.

Suggested Citation

  • Du, Ding, 2019. "Forecasting credit losses with the reversal in credit spreads," Economics Letters, Elsevier, vol. 178(C), pages 95-97.
  • Handle: RePEc:eee:ecolet:v:178:y:2019:i:c:p:95-97
    DOI: 10.1016/j.econlet.2019.02.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176519300473
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econlet.2019.02.010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. David López-Salido & Jeremy C. Stein & Egon Zakrajšek, 2017. "Credit-Market Sentiment and the Business Cycle," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(3), pages 1373-1426.
    2. Jeremy C. Stein & Anil K. Kashyap, 2000. "What Do a Million Observations on Banks Say about the Transmission of Monetary Policy?," American Economic Review, American Economic Association, vol. 90(3), pages 407-428, June.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    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. Ding Du & Ou Hu, 2020. "Why does stock-market investor sentiment influence corporate investment?," Review of Quantitative Finance and Accounting, Springer, vol. 54(4), pages 1221-1246, May.

    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. Villacorta, Alonso, 2018. "Business cycles and the balance sheets of the financial and non-financial sectors," ESRB Working Paper Series 68, European Systemic Risk Board.
    2. Chatterjee, Ujjal K., 2015. "Bank liquidity creation and asset market liquidity," Journal of Financial Stability, Elsevier, vol. 18(C), pages 139-153.
    3. repec:spo:wpecon:info:hdl:2441/f4rshpf3v1umfa09lat09b1bg is not listed on IDEAS
    4. Xudong An & Saket Hegde & Harren Jan & Mete Kilic & Rodney Ramcharan, 2025. "The Fed Put and Bank Risk-Taking Evidence from the Loan Book," Working Papers 25-42, Federal Reserve Bank of Philadelphia.
    5. Arabinda Basistha, 2023. "Estimation of short‐run predictive factor for US growth using state employment data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 34-50, January.
    6. Thiago Revil T. Ferreira, 2022. "Cross-Sectional Financial Conditions, Business Cycles and The Lending Channel," International Finance Discussion Papers 1335, Board of Governors of the Federal Reserve System (U.S.).
    7. Ferrara, Laurent & Mogliani, Matteo & Sahuc, Jean-Guillaume, 2022. "High-frequency monitoring of growth at risk," International Journal of Forecasting, Elsevier, vol. 38(2), pages 582-595.
    8. Montagnoli, Alberto & Mouratidis, Konstantinos & Whyte, Kemar, 2021. "Assessing the cyclical behaviour of bank capital buffers in a finance-augmented macro-economy," Journal of International Money and Finance, Elsevier, vol. 110(C).
    9. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95, May.
    10. Mr. Tobias Adrian & Peichu Xie, 2020. "The Non-U.S. Bank Demand for U.S. Dollar Assets," IMF Working Papers 2020/101, International Monetary Fund.
    11. Paul Hubert, 2010. "Monetary policy, imperfect information and the expectations channel [Politique monétaire,information imparfaite et canal des anticipations]," Sciences Po Economics Publications (main) tel-04095385, HAL.
    12. repec:spo:wpmain:info:hdl:2441/f4rshpf3v1umfa09lat09b1bg is not listed on IDEAS
    13. Hauzenberger, Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2025. "Bayesian neural networks for macroeconomic analysis," Journal of Econometrics, Elsevier, vol. 249(PC).
    14. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    15. Vitek, Francis, 2006. "Measuring the Stance of Monetary Policy in a Small Open Economy: A Dynamic Stochastic General Equilibrium Approach," MPRA Paper 802, University Library of Munich, Germany.
    16. Xilong Chen & Eric Ghysels, 2011. "News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons," The Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 46-81, October.
    17. Faria, Gonçalo & Verona, Fabio, 2023. "Forecast combination in the frequency domain," Bank of Finland Research Discussion Papers 1/2023, Bank of Finland.
    18. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    19. Cavit Pakel & Neil Shephard & Kevin Sheppard & Robert F. Engle, 2021. "Fitting Vast Dimensional Time-Varying Covariance Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 652-668, July.
    20. Kubin, Ingrid & Zörner, Thomas O. & Gardini, Laura & Commendatore, Pasquale, 2019. "A credit cycle model with market sentiments," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 159-174.
    21. Bentes, Sonia R. & Menezes, Rui, 2013. "On the predictability of realized volatility using feasible GLS," Journal of Asian Economics, Elsevier, vol. 28(C), pages 58-66.
    22. Hayashi, Masayoshi, 2014. "Forecasting welfare caseloads: The case of the Japanese public assistance program," Socio-Economic Planning Sciences, Elsevier, vol. 48(2), pages 105-114.

    More about this item

    Keywords

    ;
    ;

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:eee:ecolet:v:178:y:2019:i:c:p:95-97. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.