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Orthogonal Methods for Generating Large Positive Semi-Definite Covariance Matrices

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  • Carol Alexander

    ()
    (ICMA Centre, University of Reading)

Abstract

It is a common problem in risk management today that risk measures and pricing models are being applied to a very large set of scenarios based on movements in all possible risk factors. The dimensions are so large that the computations become extremely slow and cumbersome, so it is quite common that over-simplistic assumptions will be made. In particular, in order to generate the large covariance matrices that are used in Value-at-Risk models, some very strong constraints are imposed on the movements in volatility and correlations in all the standard models. The constant volatility assumption is also imposed, because it has not been possible to generate large GARCH covariance matrices with mean-reverting term structures.

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Bibliographic Info

Paper provided by Henley Business School, Reading University in its series ICMA Centre Discussion Papers in Finance with number icma-dp2000-06.

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Length: 23 pages
Date of creation: 2000
Date of revision:
Handle: RePEc:rdg:icmadp:icma-dp2000-06

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  1. Engle, Robert F. & Ng, Victor K. & Rothschild, Michael, 1990. "Asset pricing with a factor-arch covariance structure : Empirical estimates for treasury bills," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 213-237.
  2. Brailsford, Timothy J. & Faff, Robert W., 1996. "An evaluation of volatility forecasting techniques," Journal of Banking & Finance, Elsevier, vol. 20(3), pages 419-438, April.
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Cited by:
  1. Panayiotis Diamandis & Georgios Kouretas & Leonidas Zarangas, 2006. "Asset allocation in the Athens Stock Exchange: A variance sensitivity analysis," Working Papers 0602, University of Crete, Department of Economics.
  2. Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2009. "On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models," Cahiers de recherche 0948, CIRPEE.
  3. Marshall, Andrew & Maulana, Tubagus & Tang, Leilei, 2009. "The estimation and determinants of emerging market country risk and the dynamic conditional correlation GARCH model," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 250-259, December.
  4. Borgsen, Sina & Glaser, Markus, 2005. "Diversifikationseffekte durch Small und Mid Caps?," Sonderforschungsbereich 504 Publications 05-10, Sonderforschungsbereich 504, Universität Mannheim & Sonderforschungsbereich 504, University of Mannheim.

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