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Business cycle effects on Portfolio Credit Risk: scenario generation through Dynamic Factor analysis

Author

Listed:
  • rea cipollini

    (queen mary university of london)

  • giuseppe missaglia

    (iccrea)

Abstract

In this paper, we focus on measuring the risk associated to a bank loan portfolio. In particular, we depart from the standard one factor model representation of portfolio credit risk. In particular, we consider an hetrogeneous portfolio, and we account for stochastic dependent recoveries. We also examine the influence of either one systemic shock (interpreted as the state of the business cycle) or two systemic shocks (interpreted as demand and supply innovations) on portfolio credit risk. The identification and estimation of the common shocks is obtained by fitting a Dynamic Factor model to a large number of macro credit drivers. The scenarios are obtained by employing Montecarlo stochastic simulation.

Suggested Citation

  • rea cipollini & giuseppe missaglia, 2005. "Business cycle effects on Portfolio Credit Risk: scenario generation through Dynamic Factor analysis," Finance 0502010, EconWPA.
  • Handle: RePEc:wpa:wuwpfi:0502010
    Note: Type of Document - pdf; pages: 21
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    File URL: http://econwpa.repec.org/eps/fin/papers/0502/0502010.pdf
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    References listed on IDEAS

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    1. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    2. Pesaran, M. Hashem & Schuermann, Til & Treutler, Bjorn-Jakob & Weiner, Scott M., 2006. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1211-1261, August.
    3. Nickell, Pamela & Perraudin, William & Varotto, Simone, 2000. "Stability of rating transitions," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 203-227, January.
    4. Giannone, Domenico & Reichlin, Lucrezia & Sala, Luca, 2006. "VARs, common factors and the empirical validation of equilibrium business cycle models," Journal of Econometrics, Elsevier, vol. 132(1), pages 257-279, May.
    5. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    6. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
    7. Andrew G Haldane & Glenn Hoggarth & Victoria Saporta, 2001. "Assessing financial system stability, efficiency and structure at the Bank of England," BIS Papers chapters,in: Bank for International Settlements (ed.), Marrying the macro- and micro-prudential dimensions of financial stability, volume 1, pages 138-159 Bank for International Settlements.
    8. Forni, Mario & Lippi, Marco & Reichlin, Lucrezia, 2003. "Opening the Black Box: Structural Factor Models versus Structural VARs," CEPR Discussion Papers 4133, C.E.P.R. Discussion Papers.
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    Cited by:

    1. Gabriel Illanes & Alejandro Pena & Andrés Sosa, 2014. "Un Modelo Macroeconómico del Riesgo de Crédito en Uruguay," Documentos de trabajo 2014002, Banco Central del Uruguay.
    2. Petr Jakubík, 2006. "Does Credit Risk Vary with Economic Cycles? The Case of Finland," Working Papers IES 2006/11, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2006.

    More about this item

    Keywords

    Risk management default correlation Dynamic Factor;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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