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Multi-Period Structural Model of a Mortgage Portfolio with Cointegrated Factors

Author

Listed:
  • Petr Gapko

    (Econometric Department, Institute of Information Theory and Automation, Czech Academy of Sciences, Prague)

  • Martin Smid

    (Econometric Department, Institute of Information Theory and Automation, Czech Academy of Sciences, Prague)

Abstract

We propose a new dynamic two-factor model of a loan portfolio. Following the common approach, we quantify the credit risk associated with the portfolio by the probability of default and the loss given default, each of which is driven by a factor common for all debts in the portfolio, and a factor individual to each debt. In line with the empirical evidence, the individual factors are assumed to be AR(1) processes. The common factors, on the other hand, may be dependent on the external (macroeconomic) environment. We apply our model to the US nationwide mortgage portfolio, fitting the dynamics of the factors with a VECM model with several macroeconomic indicators as exogenous variables.

Suggested Citation

  • Petr Gapko & Martin Smid, 2016. "Multi-Period Structural Model of a Mortgage Portfolio with Cointegrated Factors," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(6), pages 565-574, December.
    • Handle: RePEc:fau:fauart:v:66:y:2016:i:6:p:565-574
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    References listed on IDEAS

    as
    1. 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.
    2. repec:zbw:bofrdp:2004_018 is not listed on IDEAS
    3. Jiménez, Gabriel & Mencía, Javier, 2009. "Modelling the distribution of credit losses with observable and latent factors," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 235-253, March.
    4. Per Asberg Sommar & Hovick Shahnazarian, 2009. "Interdependencies between Expected Default Frequency and the Macro Economy," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 83-110, September.
    5. Petr Gapko & Martin Šmíd, 2010. "Modeling a Distribution of Mortgage Credit Losses," Working Papers IES 2010/23, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2010.
    6. 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.
    7. Stefan Hochguertel & Henry Ohlsson, 2011. "Wealth mobility and dynamics over entire individual working life cycles," BCL working papers 56, Central Bank of Luxembourg.
    8. Jon Frye, 2000. "Collateral damage detected," Emerging Issues, Federal Reserve Bank of Chicago, issue Sep.
    9. Frontczak, Robert & Rostek, Stefan, 2015. "Modeling loss given default with stochastic collateral," Economic Modelling, Elsevier, vol. 44(C), pages 162-170.
    10. Petr Gapko & Martin Smid, 2012. "Dynamic Multi-Factor Credit Risk Model with Fat-Tailed Factors," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(2), pages 125-140, May.
    11. repec:czx:journl:v:18:y:2011:i:28:id:183 is not listed on IDEAS
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    More about this item

    Keywords

    credit risk; mortgage; loan portfolio; dynamic model; estimation;
    All these keywords.

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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