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Ratingmodell zur Quantifizierung des Ausfallrisikos von LBO-Finanzierungen

Author

Listed:
  • Lang, Michael
  • Cremers, Heinz
  • Hentze, Rainald

Abstract

Credit risk measurement and management become more important in all financial institutions in the light of the current financial crisis and the global recession. This particularly applies to most of the complex structured financing forms whose risk cannot be quantified with com-mon rating methods. This paper explains the risk associated with leveraged buyout (LBO) transactions and demon-strates the implementation of a new rating method based on a logistic regression (logit func-tion), a rating system commonly used by banks. The system estimates probabilities of default for various time horizons between three months and two years. Input variables contain information about the transaction (based on financial covenants) as well as macroeconomic parameters. The most important factor is a firm’s cyclicality. Leve-rage and capital structure are statistically significant and are also utilized in this ratings sys-tem, however they are far less important compared to cyclicality when this method is em-ployed. The validation results demonstrate a very good calibration and discriminatory power between defaulting and non-defaulting LBO transactions.

Suggested Citation

  • Lang, Michael & Cremers, Heinz & Hentze, Rainald, 2010. "Ratingmodell zur Quantifizierung des Ausfallrisikos von LBO-Finanzierungen," Frankfurt School - Working Paper Series 136, Frankfurt School of Finance and Management.
  • Handle: RePEc:zbw:fsfmwp:136
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    More about this item

    Keywords

    Logistic Regression; Logit; Credit Risk; Credit Risk Modeling; Rating; Probabili-ty of Default; PD; Basel II; Rating Validation; Rseudo-R-Square; Alpha Error; Beta Error; Minimum Classification Error; Cumulative Accuracy Profile Curve; CAP; Receiver Operating Characteristic; ROC; Area Under the Curve; AUC; Brier Score; Bootstrapping; Leveraged Buyout; LBO; Buyout; Leveraged Finance; Private Equity;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G01 - Financial Economics - - General - - - Financial Crises
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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