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Numerical estimates of risk factors contingent on credit ratings

Author

Listed:
  • T. Gärtner

    (Provincial Statistics Institute (ASTAT), Autonomous Province of Bolzano-South Tyrol)

  • S. Kaniovski

    (Austrian Institute for Economic Research (WIFO))

  • Y. Kaniovski

    (Free University of Bozen-Bolzano)

Abstract

Assuming a favorable or an adverse outcome for every combination of a credit class and an industry sector, a binary string, termed as a macroeconomic scenario, is considered. Given historical transition counts and a model for dependence among credit-rating migrations, a probability is assigned to each of the scenarios by maximizing a likelihood function. Applications of this distribution in financial risk analysis are suggested. Two classifications are considered: 7 non-default credit classes with 6 industry sectors and 2 non-default credit classes with 12 industry sectors. We propose a heuristic algorithm for solving the corresponding maximization problems of combinatorial complexity. Probabilities and correlations characterizing riskiness of random events involving several industry sectors and credit classes are reported.

Suggested Citation

  • T. Gärtner & S. Kaniovski & Y. Kaniovski, 2021. "Numerical estimates of risk factors contingent on credit ratings," Computational Management Science, Springer, vol. 18(4), pages 563-589, October.
    • Handle: RePEc:spr:comgts:v:18:y:2021:i:4:d:10.1007_s10287-021-00405-9
    DOI: 10.1007/s10287-021-00405-9
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    1. Fama, Eugene F. & French, Kenneth R., 2017. "International tests of a five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 123(3), pages 441-463.
    2. Ilan Cooper & Paulo Maio, 2019. "Asset Growth, Profitability, and Investment Opportunities," Management Science, INFORMS, vol. 65(9), pages 3988-4010, September.
    3. McNeil, Alexander J. & Wendin, Jonathan P., 2007. "Bayesian inference for generalized linear mixed models of portfolio credit risk," Journal of Empirical Finance, Elsevier, vol. 14(2), pages 131-149, March.
    4. Dmitri Boreiko & Serguei Kaniovski & Yuri Kaniovski & Georg Pflug, 2017. "Traces of business cycles in credit-rating migrations," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-29, April.
    5. Manfred Gilli & Enrico Schumann, 2012. "Heuristic optimisation in financial modelling," Annals of Operations Research, Springer, vol. 193(1), pages 129-158, March.
    6. Paul Glasserman & Peyton Young, 2015. "Contagion in Financial Networks," Economics Series Working Papers 764, University of Oxford, Department of Economics.
    7. Xing, Haipeng & Sun, Ning & Chen, Ying, 2012. "Credit rating dynamics in the presence of unknown structural breaks," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 78-89.
    8. Wozabal, David & Hochreiter, Ronald, 2012. "A coupled Markov chain approach to credit risk modeling," Journal of Economic Dynamics and Control, Elsevier, vol. 36(3), pages 403-415.
    9. Andrei S Gonçalves & Chen Xue & Lu Zhang & Stijn Van Nieuwerburgh, 2020. "Aggregation, Capital Heterogeneity, and the Investment CAPM," The Review of Financial Studies, Society for Financial Studies, vol. 33(6), pages 2728-2771.
    10. Glasserman, Paul & Young, H. Peyton, 2016. "Contagion in financial networks," LSE Research Online Documents on Economics 68681, London School of Economics and Political Science, LSE Library.
    11. Boons, Martijn, 2016. "State variables, macroeconomic activity, and the cross section of individual stocks," Journal of Financial Economics, Elsevier, vol. 119(3), pages 489-511.
    12. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2010. "Macroeconomic risks and characteristic-based factor models," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1383-1399, June.
    13. Frydman, Halina & Schuermann, Til, 2008. "Credit rating dynamics and Markov mixture models," Journal of Banking & Finance, Elsevier, vol. 32(6), pages 1062-1075, June.
    14. Glasserman, Paul & Young, H. Peyton, 2015. "How likely is contagion in financial networks?," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 383-399.
    15. Fei Fei & Ana-Maria Fuertes & Elena Kalotychou, 2012. "Credit Rating Migration Risk and Business Cycles," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 39(1-2), pages 229-263, January.
    16. Mr. John Kiff & Michael Kisser & Miss Liliana B Schumacher, 2013. "Rating Through-the-Cycle: What does the Concept Imply for Rating Stability and Accuracy?," IMF Working Papers 2013/064, International Monetary Fund.
    17. Bangia, Anil & Diebold, Francis X. & Kronimus, Andre & Schagen, Christian & Schuermann, Til, 2002. "Ratings migration and the business cycle, with application to credit portfolio stress testing," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 445-474, March.
    18. Kaniovski, Y.M. & Pflug, G.Ch., 2007. "Risk assessment for credit portfolios: A coupled Markov chain model," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2303-2323, August.
    19. Paul Glasserman & H. Peyton Young, 2016. "Contagion in Financial Networks," Journal of Economic Literature, American Economic Association, vol. 54(3), pages 779-831, September.
    20. Stefanescu, Catalina & Tunaru, Radu & Turnbull, Stuart, 2009. "The credit rating process and estimation of transition probabilities: A Bayesian approach," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 216-234, March.
    21. D. V. Boreiko & Y. M. Kaniovski & G. Ch. Pflug, 2016. "Modeling dependent credit rating transitions: a comparison of coupling schemes and empirical evidence," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(4), pages 989-1007, December.
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