EVALUATING CREDIT RISK MODELS
DOI:
https://doi.org/10.53555/nnbma.v9i5.1695Keywords:
Empirical testing, Competing theories, statistical method, finite Mixture- Models, probability modelAbstract
Empirical testing of competing theories lies at the heart of social science and applied Science research. We demonstrate that a well-known class of statistical models, called finite mixture models, provides an effective way of rival theory testing. In the proposed framework, each observation is assumed to be generated either from statistical models implied by one of the competing theories or more generally from a weighted combination of multiple statistical models under consideration. Researchers can then estimate the probability that a specific observation is consistent with each rival theory. By modeling this probability with covariates, one can also explore the condition under which a particular theory applies. We discuss a principles way to identify a list of observations that are statistically consistent with each theory and propose measure of the overall performance of each competing theory. We illustrate the relatives’ advantages of our method over existing methods through empirical and stimulation studies.
References
Altman, E.I. and Saunders, A., 1997. “Credit Risk Measurement: Developments over the Last Twenty Years,” Journal of Banking and Finance, 21, 1721-1742.
Basle Committee on Banking Supervision, 1999. “Credit Risk Modelling: Current Practices and Applications,” Basle Committee on Banking Supervision, Basle. (http://www.bis.org/press/index.htm)
Berkowitz, J., 1999. “Evaluating the Forecasts of Risk Models,” Manuscript, Trading Risk Analysis Group, Federal Reserve Board of Governors.
Carey, M., 1998. “Credit Risk in Private Debt Portfolios,” Journal of Finance, 53, 1363-1388. Credit Suisse Financial Products, 1997. CreditRisk+: A Credit Risk Management Framework.
a. (http://www.csfp.co.uk/csfpfod/html/csfp_10.htm).
Crnkovic, C. and Drachman, J., 1996. “Quality Control,” Risk, 9, 139-143.
Crouhy, M. and Mark, R., 1998. “A Comparative Analysis of Current Credit Risk Models,” Manuscript, Conference on Credit Risk Modelling and Regulatory Implications.
Diebold, F.X., Gunther, T.A. and Tay, A.S., 1997. “Evaluating Density Forecasts with Applications to Financial Risk Management,” International Economic Review, 39, 863-883.
Diebold, F.X., Hahn, J. and Tay, A.S., 1998. “Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange,” Manuscript, Department of Economic, University of Pennsylvania.
Diebold, F.X. and Lopez, J.A., 1996. "Forecast Evaluation and Combination," in Maddala, G.S. and Rao, C.R., eds., Handbook of Statistics, Volume 14: Statistical Methods in Finance, 241-268. Amsterdam: North-Holland.
Diebold, F.X. and Mariano, R., 1995. "Comparing Predictive Accuracy," Journal of Business and Economic Statistics, 13, 253-264.
Federal Reserve System Task Force on Internal Credit Risk Models, 1998. “Credit Risk Models at Major U.S. Banking Institutions: Current State of the Art and Implications for Assessments of Capital Adequacy.” Manuscript, Board of Governors of the Federal Reserve System. (http://www.federalreserve.gov:80/boarddocs/press/General/1998/ 19980529/study.pdf)
Gordy, M.B., 1998. “A Comparative Anatomy of Credit Risk Models,” Manuscript, Conference on Credit Risk Modelling and Regulatory Implications.
Granger, C.W.J. and Huang, L.-L., 1997. “Evaluation of Panel Data Models: Some Suggestions from Time Series,” Discussion Paper 97-10, Department of Economics, University of California, San Diego.
International Swaps and Derivatives Association, 1998. Credit Risk and Regulatory Capital.
a. (http://www.isda.org/crsk0398.pdf).
The Institute of International Finance Working Group on Capital Adequacy, 1998. “Report of the Working Group on Capital Adequacy – Recommendations for Revising the Regulatory Capital Rules for Credit Risk” The Institute of International Finance, Inc.
J.P. Morgan, 1998. CreditMetrics - Technical Document. (http://riskmetrics.com/cm/pubs/ CMTD1.pdf)
Koyluoglu, H.U. and Hickman, A., 1998. “A Generalized Framework for Credit Risk Portfolio Models,” Manuscript, Oliver Wyman & Company.
Kupiec, P., 1995. “Techniques for Verifying the Accuracy of Risk Measurement Models,”
a. Journal of Derivatives, 3, 73-84.
Lopez, J.A., 1999a. “Regulatory Evaluation of Value-at-Risk Models,” Journal of Risk, forthcoming.
Lopez, J.A., 1999b. “Methods for Evaluating Value-at-Risk Estimates,” Federal Reserve Bank of San Francisco Economic Review, forthcoming.
Nickell, P., Perraudin, W., and Varotto, S., 1998. “Ratings- Versus Equity-Based Credit Risk Modelling: An Empirical Analysis.” Manuscript, Conference on Credit Risk Modelling and Regulatory Implications.
Treacy W.F. and Carey, M..,1998. “Credit Risk Rating at Large U.S. Banks,” Federal Reserve Bulletin, 897-921.
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