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Structural Credit Modelling and Its Relationship to Market Value at Risk: An Australian Sectoral Perspective

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Listed:
  • Allen, David E
  • Powell, Robert

Abstract

Credit risk modelling has become increasingly important to Banks since the advent of Basel II which allows Banks with sophisticated modelling techniques to use internal models for the purpose of calculating capital requirements. A high level of credit risk is often the key reason behind banks failing or experiencing severe difficulty. The management of sectoral concentration is a critical component of credit risk management, as over concentration of credit in sectors can be a significant contributor to difficulties experienced by Banks. Conditional Value at Risk (CVaR) is gaining popularity as a measurement of credit risk, with the recognition that high lending losses are often impacted by a small number of extreme events. This study examines sectoral probability of default (PD) in an Australian context based on the structural approach of Merton (1974), and more recently modified and popularised by KMV Corporation (Crosbie & Bohn, 2003). In addition to examining PD, we introduce a CVaR type component into structural modelling which we term conditional probability of default (CPD). We also examine the interaction between sectoral credit and market risk using VaR and CVaR models for market risk, and PD and CPD models for credit risk. Significant rank correlation is found between all of the approaches used, showing that those sectors which are risky from a credit perspective are not significantly different from those which are risky from a market perspective.

Suggested Citation

  • Allen, David E & Powell, Robert, 2008. "Structural Credit Modelling and Its Relationship to Market Value at Risk: An Australian Sectoral Perspective," MPRA Paper 47206, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:47206
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    File URL: https://mpra.ub.uni-muenchen.de/47206/1/MPRA_paper_13822.pdf
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    References listed on IDEAS

    as
    1. Robert A. Jarrow & David Lando & Stuart M. Turnbull, 2008. "A Markov Model for the Term Structure of Credit Risk Spreads," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 18, pages 411-453, World Scientific Publishing Co. Pte. Ltd..
    2. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    3. David E. Allen & Robert Powell, 2009. "Transitional credit modelling and its relationship to market value at risk: an Australian sectoral perspective," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 49(3), pages 425-444, September.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Vo, D.H. & Tran, N.P. & Duong, T.N.-T. & McAleer, M.J., 2019. "Risk Analysis of Energy in Vietnam," Econometric Institute Research Papers EI2019-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Ngoc Phu Tran & Thang Cong Nguyen & Duc Hong Vo & Michael McAleer, 2019. "Market Risk Analysis of Energy in Vietnam," Risks, MDPI, vol. 7(4), pages 1-13, November.
    3. Allen, D.E. & Powell, R.J. & Singh, A.K., 2016. "Take it to the limit: Innovative CVaR applications to extreme credit risk measurement," European Journal of Operational Research, Elsevier, vol. 249(2), pages 465-475.

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    More about this item

    Keywords

    Value at risk; Conditional value at risk; Credit risk; Conditional probabilities of default; Structural modelling;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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