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Estimation of the conditional variance-covariance matrix of returns using the intraday range

  • Harris, Richard D.F.
  • Yilmaz, Fatih

This paper proposes a hybrid multivariate exponentially weighted moving average (EWMA) estimator of the variance-covariance matrix of returns. The proposed estimator employs a range-based EWMA specification to estimate the conditional variances of returns, and a standard return-based EWMA specification to estimate the correlation between each pair of returns. The hybrid EWMA estimator offers an improvement over the standard EWMA estimator, both statistically and economically. Moreover, the hybrid EWMA estimator is less sensitive to the choice of decay factor.

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Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 26 (2010)
Issue (Month): 1 (January)
Pages: 180-194

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Handle: RePEc:eee:intfor:v:26:y::i:1:p:180-194
Contact details of provider: Web page: http://www.elsevier.com/locate/ijforecast

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  1. Brandt, Michael W. & Jones, Christopher S., 2006. "Volatility Forecasting With Range-Based EGARCH Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 470-486, October.
  2. Michael W. Brandt & Francis X. Diebold, 2001. "A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations," PIER Working Paper Archive 03-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Apr 2003.
  3. Chou, Ray Yeutien, 2005. "Forecasting Financial Volatilities with Extreme Values: The Conditional Autoregressive Range (CARR) Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 561-82, June.
  4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
  5. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
  6. Martens, M.P.E. & van Dijk, D.J.C., 2006. "Measuring volatility with the realized range," Econometric Institute Research Papers EI 2006-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  7. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
  8. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
  9. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
  10. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range-Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, 06.
  11. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
  12. Christensen, Kim & Podolskij, Mark, 2007. "Realized range-based estimation of integrated variance," Journal of Econometrics, Elsevier, vol. 141(2), pages 323-349, December.
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