IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v32y2020ics1544612318300357.html
   My bibliography  Save this article

Predicting default rates by capturing critical transitions in the macroeconomic system

Author

Listed:
  • Xing, Kai
  • Yang, Xiaoguang

Abstract

We employ a method of capturing critical transitions of macroeconomic system to predict corporate default. The method is originally developed for anticipating critical transitions in complex natural systems. Based on this method, we construct macro-indicators for capturing incipient changes in the macroeconomic system by using different sets of economic factors, and then we use these indicators to predict corporate default in the US industrial sector. Empirical results show that the indicator constructed by exclusively using leading factors outperforms the other indicators in terms of predicting power. This study implies that the method proposed in natural sciences can be extended efficiently to the field of economics, and it is not the interaction of more variables but the interaction of the leading variables to contain more important information.

Suggested Citation

  • Xing, Kai & Yang, Xiaoguang, 2020. "Predicting default rates by capturing critical transitions in the macroeconomic system," Finance Research Letters, Elsevier, vol. 32(C).
    • Handle: RePEc:eee:finlet:v:32:y:2020:i:c:s1544612318300357
    DOI: 10.1016/j.frl.2019.02.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612318300357
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2019.02.007?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Mark Gertler, 1988. "Financial structure and aggregate economic activity: an overview," Proceedings, Federal Reserve Bank of Cleveland, pages 559-596.
    2. Geoffrey H. Moore, 1961. "Statistical Indicators of Cyclical Revivals and Recessions," NBER Chapters, in: Business Cycle Indicators, Volume 1, pages 184-260, National Bureau of Economic Research, Inc.
    3. Heikki Kauppi & Pentti Saikkonen, 2008. "Predicting U.S. Recessions with Dynamic Binary Response Models," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 777-791, November.
    4. Darrell Duffie & Andreas Eckner & Guillaume Horel & Leandro Saita, 2009. "Frailty Correlated Default," Journal of Finance, American Finance Association, vol. 64(5), pages 2089-2123, October.
    5. Koopman, Siem Jan & Kräussl, Roman & Lucas, André & Monteiro, André B., 2009. "Credit cycles and macro fundamentals," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 42-54, January.
    6. Geoffrey H. Moore & Julius Shiskin, 1967. "Indicators of Business Expansions and Contractions," NBER Books, National Bureau of Economic Research, Inc, number moor67-2.
    7. Gorban, Alexander N. & Smirnova, Elena V. & Tyukina, Tatiana A., 2010. "Correlations, risk and crisis: From physiology to finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3193-3217.
    8. Hackbarth, Dirk & Miao, Jianjun & Morellec, Erwan, 2006. "Capital structure, credit risk, and macroeconomic conditions," Journal of Financial Economics, Elsevier, vol. 82(3), pages 519-550, December.
    9. Lo, Ming Chien & Zivot, Eric, 2001. "Threshold Cointegration And Nonlinear Adjustment To The Law Of One Price," Macroeconomic Dynamics, Cambridge University Press, vol. 5(4), pages 533-576, September.
    10. Bernanke, Ben & Gertler, Mark & Gilchrist, Simon, 1996. "The Financial Accelerator and the Flight to Quality," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 1-15, February.
    11. Sanjiv R. Das & Darrell Duffie & Nikunj Kapadia & Leandro Saita, 2007. "Common Failings: How Corporate Defaults Are Correlated," Journal of Finance, American Finance Association, vol. 62(1), pages 93-117, February.
    12. Lando, David & Nielsen, Mads Stenbo, 2010. "Correlation in corporate defaults: Contagion or conditional independence?," Journal of Financial Intermediation, Elsevier, vol. 19(3), pages 355-372, July.
    13. Ben S. Bernanke, 1993. "Credit in the macroeconomy," Quarterly Review, Federal Reserve Bank of New York, vol. 18(Spr), pages 50-70.
    14. A. N. Gorban & E. V. Smirnova & T. A. Tyukina, 2009. "Correlations, Risk and Crisis: From Physiology to Finance," Papers 0905.0129, arXiv.org, revised Aug 2010.
    15. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    16. Hui Chen, 2010. "Macroeconomic Conditions and the Puzzles of Credit Spreads and Capital Structure," Journal of Finance, American Finance Association, vol. 65(6), pages 2171-2212, December.
    17. Jordan, Bradford D & Jordan, Susan D, 1997. "Special Repo Rates: An Empirical Analysis," Journal of Finance, American Finance Association, vol. 52(5), pages 2051-2072, December.
    18. Azizpour, S & Giesecke, K. & Schwenkler, G., 2018. "Exploring the sources of default clustering," Journal of Financial Economics, Elsevier, vol. 129(1), pages 154-183.
    19. Dirk Helbing, 2013. "Globally networked risks and how to respond," Nature, Nature, vol. 497(7447), pages 51-59, May.
    20. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    21. Koopman, Siem Jan & Lucas, André & Schwaab, Bernd, 2011. "Modeling frailty-correlated defaults using many macroeconomic covariates," Journal of Econometrics, Elsevier, vol. 162(2), pages 312-325, June.
    22. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    23. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 95-156, National Bureau of Economic Research, Inc.
    24. Annelies J. Veraart & Elisabeth J. Faassen & Vasilis Dakos & Egbert H. van Nes & Miquel Lürling & Marten Scheffer, 2012. "Correction: Corrigendum: Recovery rates reflect distance to a tipping point in a living system," Nature, Nature, vol. 484(7394), pages 404-404, April.
    25. Ng, Eric C.Y., 2012. "Forecasting US recessions with various risk factors and dynamic probit models," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 112-125.
    26. Marten Scheffer & Jordi Bascompte & William A. Brock & Victor Brovkin & Stephen R. Carpenter & Vasilis Dakos & Hermann Held & Egbert H. van Nes & Max Rietkerk & George Sugihara, 2009. "Early-warning signals for critical transitions," Nature, Nature, vol. 461(7260), pages 53-59, September.
    27. Annelies J. Veraart & Elisabeth J. Faassen & Vasilis Dakos & Egbert H. van Nes & Miquel Lürling & Marten Scheffer, 2012. "Recovery rates reflect distance to a tipping point in a living system," Nature, Nature, vol. 481(7381), pages 357-359, 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. Xing, Kai & Luo, Dan & Liu, Lanlan, 2023. "Macroeconomic conditions, corporate default, and default clustering," Economic Modelling, Elsevier, vol. 118(C).

    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. Xing, Kai & Luo, Dan & Liu, Lanlan, 2023. "Macroeconomic conditions, corporate default, and default clustering," Economic Modelling, Elsevier, vol. 118(C).
    2. Nguyen, Ha, 2023. "An empirical application of Particle Markov Chain Monte Carlo to frailty correlated default models," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 103-121.
    3. Bernd Schwaab & Siem Jan Koopman & André Lucas, 2017. "Global Credit Risk: World, Country and Industry Factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 296-317, March.
    4. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2014. "Nowcasting and forecasting global financial sector stress and credit market dislocation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 741-758.
    5. Anna Dubinova & Andre Lucas & Sean Telg, 2021. "COVID-19, Credit Risk and Macro Fundamentals," Tinbergen Institute Discussion Papers 21-059/III, Tinbergen Institute.
    6. Xiao, Tim, 2018. "The Valuation of Credit Default Swap with Counterparty Risk and Collateralization," EconStor Preprints 203447, ZBW - Leibniz Information Centre for Economics.
    7. Xiao,Tim, 2018. "Pricing Financial Derivatives Subject to Multilateral Credit Risk and Collateralization," EconStor Preprints 202075, ZBW - Leibniz Information Centre for Economics.
    8. Mark Clintworth & Dimitrios Lyridis & Evangelos Boulougouris, 2023. "Financial risk assessment in shipping: a holistic machine learning based methodology," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 25(1), pages 90-121, March.
    9. Tor Jacobson & Jesper Lindé & Kasper Roszbach, 2013. "Firm Default And Aggregate Fluctuations," Journal of the European Economic Association, European Economic Association, vol. 11(4), pages 945-972, August.
    10. Alan White, 2018. "Pricing Credit Default Swap Subject to Counterparty Risk and Collateralization," Working Papers hal-01739310, HAL.
    11. Jennie Bai & Pierre Collin-Dufresne & Robert S. Goldstein & Jean Helwege, 2012. "On bounding credit event risk premia," Staff Reports 577, Federal Reserve Bank of New York.
    12. Bátiz-Zuk Enrique & Mohamed Abdulkadir & Sánchez-Cajal Fátima, 2021. "Exploring the sources of loan default clustering using survival analysis with frailty," Working Papers 2021-14, Banco de México.
    13. Xiao, Tim, 2013. "The Impact of Default Dependency and Collateralization on Asset Pricing and Credit Risk Modeling," MPRA Paper 47136, University Library of Munich, Germany.
    14. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    15. Qi, Min & Zhang, Xiaofei & Zhao, Xinlei, 2014. "Unobserved systematic risk factor and default prediction," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 216-227.
    16. James Wolter, 2013. "Separating the impact of macroeconomic variables and global frailty in event data," Economics Series Working Papers 667, University of Oxford, Department of Economics.
    17. François Gourio, 2013. "Credit Risk and Disaster Risk," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(3), pages 1-34, July.
    18. Geir D. Berentsen & Jan Bulla & Antonello Maruotti & Bård Støve, 2022. "Modelling clusters of corporate defaults: Regime‐switching models significantly reduce the contagion source," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 698-722, June.
    19. Lee, Yongwoong & Rösch, Daniel & Scheule, Harald, 2021. "Systematic credit risk in securitised mortgage portfolios," Journal of Banking & Finance, Elsevier, vol. 122(C).
    20. Tim, Xiao, 2019. "Pricing Credit Default Swap Subject to Counterparty Risk and Collateralization," MPRA Paper 94701, University Library of Munich, Germany.

    More about this item

    Keywords

    Corporate default; Macro-indicator; Critical transitions;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • 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:finlet:v:32:y:2020:i:c:s1544612318300357. 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/frl .

    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.