Stress Testing Banks' Credit Risk Using Mixture Vector Autoregressive Models
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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- 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.
- Markku Lanne & Pentti Saikkonen, 2001. "Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes," CeNDEF Workshop Papers, January 2001 PO5, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- Lanne, Markku & Saikkonen, Pentti, 2000. "Modeling the US short-term interest rate by mixture autoregressive processes," SFB 373 Discussion Papers 2000,76, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Markku Lanne, 2006.
"Nonlinear dynamics of interest rate and inflation,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 21(8), pages 1157-1168.
- Armando MÃ©ndez Morales & Jose Giancarlo Gasha, 2004. "Identifying Threshold Effects in Credit Risk Stress Testing," IMF Working Papers 04/150, International Monetary Fund.
- 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.
- Marco Sorge, 2004. "Stress-testing financial systems: an overview of current methodologies," BIS Working Papers 165, Bank for International Settlements.
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