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Comparing simulation models for market risk stress testing

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  • Basu, Sanjay
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    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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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 213 (2011)
    Issue (Month): 1 (August)
    Pages: 329-339

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    Handle: RePEc:eee:ejores:v:213:y:2011:i:1:p:329-339

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    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: Risk management Volatility updation Tail diversification Simulation models Fat-tailed distributions;

    References

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    Cited by:
    1. 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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