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Comparing simulation models for market risk stress testing

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  • Basu, Sanjay

Abstract

The subprime crisis has reminded us that effective stress tests should not only combine subjective scenarios with historical data, but also be probabilistic. In this paper, we combine three hypothetical shocks, of varying degrees, with more than six years of daily data on USD-INR and Euro-INR. Our objective is to compare six simulation-based stress models for foreign exchange positions. We find that while volatility-weighted historical simulation is the best model for volatility persistence, jump diffusion based Monte Carlo simulation is better at capturing correlation breakdown. Loss estimates from very fat-tailed distributions are not sensitive to the severity of stress scenarios.

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  • Basu, Sanjay, 2011. "Comparing simulation models for market risk stress testing," European Journal of Operational Research, Elsevier, vol. 213(1), pages 329-339, August.
    • Handle: RePEc:eee:ejores:v:213:y:2011:i:1:p:329-339
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    1. Michael S. Gibson, 2001. "Incorporating event risk into value-at-risk," Finance and Economics Discussion Series 2001-17, Board of Governors of the Federal Reserve System (U.S.).
    2. Bhattacharyya, Malay & Chaudhary, Abhishek & Yadav, Gaurav, 2008. "Conditional VaR estimation using Pearson's type IV distribution," European Journal of Operational Research, Elsevier, vol. 191(2), pages 386-397, December.
    3. Grundke, Peter, 2009. "Importance sampling for integrated market and credit portfolio models," European Journal of Operational Research, Elsevier, vol. 194(1), pages 206-226, April.
    4. Koenig, Matthias & Meissner, Joern, 2010. "List pricing versus dynamic pricing: Impact on the revenue risk," European Journal of Operational Research, Elsevier, vol. 204(3), pages 505-512, August.
    5. Patnaik, Ila & Shah, Ajay, 2010. "Why India Choked when Lehman Broke," India Policy Forum, National Council of Applied Economic Research, vol. 6(1), pages 39-72.
    6. Hai Lan & Barry L. Nelson & Jeremy Staum, 2010. "A Confidence Interval Procedure for Expected Shortfall Risk Measurement via Two-Level Simulation," Operations Research, INFORMS, vol. 58(5), pages 1481-1490, October.
    7. Dimson, Elroy & Marsh, Paul, 1997. "Stress tests of capital requirements," Journal of Banking & Finance, Elsevier, vol. 21(11-12), pages 1515-1546, December.
    8. Jeremy Berkowitz, 1999. "A coherent framework for stress-testing," Finance and Economics Discussion Series 1999-29, Board of Governors of the Federal Reserve System (U.S.).
    9. Haldane, Andrew & Hall, Simon & Pezzini, Silvia, 2007. "Financial Stability Paper No 2: A New Approach to Assessing Risks to Financial Stability," Bank of England Financial Stability Papers 2, Bank of England.
    10. Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
    11. Homburg, Carsten & Scherpereel, Peter, 2008. "How should the cost of joint risk capital be allocated for performance measurement?," European Journal of Operational Research, Elsevier, vol. 187(1), pages 208-227, May.
    12. Bali, Turan G. & Neftci, Salih N., 2003. "Disturbing extremal behavior of spot rate dynamics," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 455-477, September.
    13. Bank for International Settlements, 2005. "Stress testing at major financial institutions: survey results and practice," CGFS Papers, Bank for International Settlements, number 24, december.
    14. Mr. Mark Swinburne & Stéphanie Marie Stolz & Ms. Marina Moretti, 2008. "Stress Testing at the IMF," IMF Working Papers 2008/206, International Monetary Fund.
    15. Huang, Dashan & Zhu, Shushang & Fabozzi, Frank J. & Fukushima, Masao, 2010. "Portfolio selection under distributional uncertainty: A relative robust CVaR approach," European Journal of Operational Research, Elsevier, vol. 203(1), pages 185-194, May.
    16. Pérignon, Christophe & Smith, Daniel R., 2010. "Diversification and Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 55-66, January.
    17. Pritsker, Matthew, 2006. "The hidden dangers of historical simulation," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 561-582, February.
    18. Alexander, Carol & Sheedy, Elizabeth, 2008. "Developing a stress testing framework based on market risk models," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2220-2236, October.
    19. Pérignon, Christophe & Smith, Daniel R., 2010. "The level and quality of Value-at-Risk disclosure by commercial banks," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 362-377, February.
    20. Bams, Dennis & Lehnert, Thorsten & Wolff, Christian C.P., 2005. "An evaluation framework for alternative VaR-models," Journal of International Money and Finance, Elsevier, vol. 24(6), pages 944-958, October.
    21. Coffinet, J. & Lin, S. & Martin, C., 2009. "Stress testing French banks' income subcomponents," Working papers 242, Banque de France.
    22. Hsieh, Chung-Chi & Lu, Yu-Ting, 2010. "Manufacturer's return policy in a two-stage supply chain with two risk-averse retailers and random demand," European Journal of Operational Research, Elsevier, vol. 207(1), pages 514-523, November.
    23. Turan G. Bali, 2003. "An Extreme Value Approach to Estimating Volatility and Value at Risk," The Journal of Business, University of Chicago Press, vol. 76(1), pages 83-108, January.
    24. Ma, Chenghu & Wong, Wing-Keung, 2010. "Stochastic dominance and risk measure: A decision-theoretic foundation for VaR and C-VaR," European Journal of Operational Research, Elsevier, vol. 207(2), pages 927-935, December.
    25. Turan G. Bali, 2007. "A Generalized Extreme Value Approach to Financial Risk Measurement," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1613-1649, October.
    26. Turan Bali & Panayiotis Theodossiou, 2007. "A conditional-SGT-VaR approach with alternative GARCH models," Annals of Operations Research, Springer, vol. 151(1), pages 241-267, April.
    27. S. Narayan, 2009. "India," Chapters, in: Peter Draper & Philip Alves & Razeen Sally (ed.), The Political Economy of Trade Reform in Emerging Markets, chapter 7, Edward Elgar Publishing.
    28. Broussard, John Paul & Booth, G. Geoffrey, 1998. "The behavior of extreme values in Germany's stock index futures: An application to intradaily margin setting," European Journal of Operational Research, Elsevier, vol. 104(3), pages 393-402, February.
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    2. Mitra, Sovan & Date, Paresh & Mamon, Rogemar & Wang, I-Chieh, 2013. "Pricing and risk management of interest rate swaps," European Journal of Operational Research, Elsevier, vol. 228(1), pages 102-111.

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