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Value At Risk Incorporating Dynamic Portfolio Management

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  • Stephen Lawrence

    (Boston College)

Abstract

Value at Risk calculations traditionally assume a fixed portfolio. However, occasionally, over a medium term horizon, a particular model of trading behavior is applicable and a dynamic portfolio should be considered for accurate VaR calculation. In this paper I describe a Monte Carlo simulation technique to calculate the distribution of portfolio returns over a several day horizon. I develop a bootstrap method for generating simulated returns from the underlying financial instruments, as well as investigate the theoretical statistical properties of the estimates. At each stage of the calculation, several behavioral trading models are considered to test the effect of back office restrictions on a portfolio manager's risk exposure. Finally, using daily currency rates, the model is tested empirically for estimation accuracy.

Suggested Citation

  • Stephen Lawrence, 2000. "Value At Risk Incorporating Dynamic Portfolio Management," Computing in Economics and Finance 2000 147, Society for Computational Economics.
  • Handle: RePEc:sce:scecf0:147
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    File URL: http://fmwww.bc.edu/cef00/papers/paper147.pdf
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    References listed on IDEAS

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    1. Ioannis Karatzas & Jaksa Cvitanic, 1999. "On dynamic measures of risk," Finance and Stochastics, Springer, vol. 3(4), pages 451-482.
    2. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    3. Basak, Suleyman & Shapiro, Alexander, 2001. "Value-at-Risk-Based Risk Management: Optimal Policies and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 371-405.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Darryll Hendricks, 1996. "Evaluation of value-at-risk models using historical data," Economic Policy Review, Federal Reserve Bank of New York, vol. 2(Apr), pages 39-69.
    6. Jeremy Berkowitz & Lutz Kilian, 2000. "Recent developments in bootstrapping time series," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 1-48.
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