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Calculating incremental risk charges: The effect of the liquidity horizon

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  • Skoglund, Jimmy
  • Chen, Wei

Abstract

The recent incremental risk charge addition to the Basel (1996) market risk amend- ment requires banks to estimate, separately, the default and migration risk of their trading portfolios that are exposed to credit risk. The new regulation requires the total regulatory charges for trading books to be computed as the sum of the market risk capi- tal and the incremental risk charge for credit risk. In contrast to Basel II models for the banking book no model is prescribed and banks can use internal models for calculating the incremental risk charge. In the calculation of incremental risk charges a key compo- nent is the choice of the liquidity horizon for traded credits. In this paper we explore the e¤ect of the liquidity horizon on the incremental risk charge. Speci�cally we consider a sample of 28 bonds with di¤erent rating and liquidity horizons to evaluate the impact of the choice of the liquidity horizon for a certain rating class of credits. We �find that choosing the liquidity horizon for a particular credit there are two important effects that needs to be considered. Firstly, for bonds with short liquidity horizons there is a miti- gation effect of preventing the bond from further downgrades by trading it frequently. Secondly, there is the possibility of multiple defaults. Of these two effects the multiple default effect will generally be more pronounced for non investment grade credits as the probability of default is severe even for short liquidity periods. For medium investment grade credits these two effects will in general o¤set and the incremental risk charge will be approximately the same across liquidity horizons. For high quality investment grade credits the effect of the multiple defaults is low for short liquidity horizons as the frequent trading effectively prevents severe downgrades.

Suggested Citation

  • Skoglund, Jimmy & Chen, Wei, 2010. "Calculating incremental risk charges: The effect of the liquidity horizon," MPRA Paper 31535, University Library of Munich, Germany, revised 10 Feb 2011.
    • Handle: RePEc:pra:mprapa:31535
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    References listed on IDEAS

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    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. Longstaff, Francis A & Schwartz, Eduardo S, 1995. "A Simple Approach to Valuing Risky Fixed and Floating Rate Debt," Journal of Finance, American Finance Association, vol. 50(3), pages 789-819, July.
    3. 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.
    4. Robert B. Israel & Jeffrey S. Rosenthal & Jason Z. Wei, 2001. "Finding Generators for Markov Chains via Empirical Transition Matrices, with Applications to Credit Ratings," Mathematical Finance, Wiley Blackwell, vol. 11(2), pages 245-265, April.
    5. Sarig, Oded & Warga, Arthur, 1989. "Bond Price Data and Bond Market Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(3), pages 367-378, September.
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    More about this item

    Keywords

    credit risk; incremental risk charge; liquidity horizon; Basel III;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General

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