Application of Nonstationary Markovian Models to Risk Management in Automobile Leasing
Chapter
Abstract
Automobile leasing is a growing and competitive business in which the lessor absorbs the risk of fluctuations in used-car prices, in addition to normal credit risks. To explore the various dimensions of risk in automobile leasing, we construct a set of integrated statistical models using account-level data from a major U.S. financial institution. Nonstationary Markovian models represent the life of a lease. A dozen logistic and regression models represent alternative paths on termination. We describe the comprehensive model and its validation, demonstrate its utility for management of credit risk, and provide new understanding about the character of the credit instrument.
Key words
Risk management Forecasting Credit Leasing Nonstationary Markov chainsPreview
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References
- ABA Banking Journal, 1997, 89 (2), 34–37Google Scholar
- Altman, E.I. Measuring Corporate Bond Mortality and Performance, Journal of Finance, 1989, 44, 909–922.CrossRefGoogle Scholar
- Asquith, P.D.W. Mullins Jr. and E.D. Wolff. Original Issue High Yield Bonds: Aging Analysis of Defaults, Exchanges, and Calls, Journal of Finance, 1989, 44, 923–953.CrossRefGoogle Scholar
- Campbell, T.S., and J.K. Dietrich. The Determinants of Default on Insured Conventional Residential Mortgage Loans, Journal of Finance, 1983, 38, 1569–1581.CrossRefGoogle Scholar
- Cunningham, D.F. and C.A. Capone Jr. The Relative Termination Experience of Adjustable to Fixed Rate Mortgages, Journal of Finance 1990, 5, 1687–1703CrossRefGoogle Scholar
- Curnow, G., G. Kochman, S. Meester, D. Sarkar, and K. Wilton. Automating Credit and CollectionsDecisions at AT&T Capital Corporation, Interfaces, 1997, 27 (1), 29–52CrossRefGoogle Scholar
- Cyert, R.M., H.J. Davidson and G.L. Thompson. Estimation of the Allowance for Doubtful Accountsby Markov Chains, Management Science, 1962, 8, 287–303.CrossRefGoogle Scholar
- Kang, P. and S. Zenios. Complete Prepayment Models for Mortgage-Backed Securities, Management Science 1992, 38, 1665–1685.CrossRefGoogle Scholar
- Lawrence, E.C., L.D. Smith and M. Rhoades. An Analysis of Default Risk in Mobile Home Credit, Journal of Banking and Finance, 1992, 16, 299–312.CrossRefGoogle Scholar
- Rosenberg, E. and A. Gleit. Quantitative Methods in Credit Management: A Survey, Operations Research, 1994, 42 (4), 589–613.CrossRefGoogle Scholar
- Smith, L.D., and E.C. Lawrence. Forecasting Losses on Liquidating Long-Term Loan Portfolio, Journal of Banking and Finance, 1995, 19, 959–985.CrossRefGoogle Scholar
- Smith, L.D., S.M. Sanchez, and E.C. Lawrence. A Comprehensive Model for Managing Risk on Home Mortgage Portfolios, Decision Sciences, 1996, 27 (2), 291–317.Google Scholar
- Smith, L.D., D. Mathew, Ya-Yung Wu, Disaggregation Strategies in Building Forecasting Models for Portfolios of Secured Loans“, Decision Sciences Institute Proceedings, San Diego, CA 1997.Google Scholar
- Zanakis, S.H., L.P. Mavrides and E.N. Roussakis. Applications of Management Science in Banking. Decision Sciences, 1986, 17, 114–128.CrossRefGoogle Scholar
- Zipkin, P. Mortgages and Markov Chains: A Simplified Valuation Model, Management Science, 1993, 39, 683–691.CrossRefGoogle Scholar
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