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Stress Testing Banks' Credit Risk Using Mixture Vector Autoregressive Models

  • Tom Pak-wing Fong

    (Research Department, Hong Kong Monetary Authority)

  • Chun-shan Wong

    (Department of Finance, The Chinese University of Hong Kong)

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    This paper estimates macroeconomic credit risk of banks¡¦ loan portfolio based on a class of mixture vector autoregressive models. Such class of models can differentiate distributions of default rates and macroeconomic conditions for different market situations and can capture their dynamics evolving over time, including the feedback effect from an increase in fragility back to the macroeconomy. These extensions can facilitate the evaluation of credit risks of loan portfolio based on different credit loss distributions.

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    Paper provided by Hong Kong Monetary Authority in its series Working Papers with number 0813.

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    Length: 23 pages
    Date of creation: Oct 2008
    Date of revision:
    Handle: RePEc:hkg:wpaper:0813
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    1. Armando Méndez Morales & Jose Giancarlo Gasha, 2004. "Identifying Threshold Effects in Credit Risk Stress Testing," IMF Working Papers 04/150, International Monetary Fund.
    2. Markku Lanne, 2004. "Nonlinear dynamics of interest rate and inflation," Macroeconomics 0405014, EconWPA.
    3. Markku Lanne & Pentti Saikkonen, 2003. "Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 1(1), pages 96-125.
    4. Marco Sorge, 2004. "Stress-testing financial systems: an overview of current methodologies," BIS Working Papers 165, Bank for International Settlements.
    5. Berchtold, Andre, 2003. "Mixture transition distribution (MTD) modeling of heteroscedastic time series," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 399-411, January.
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