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A General Volatility Framework and the Generalised Historical Volatility Estimator

Author

Listed:
  • Bollen, B.
  • Inder, B.

Abstract

This study proposes a new approach to estimation of the time series properties of daily volatility in financial markets.

Suggested Citation

  • Bollen, B. & Inder, B., 1998. "A General Volatility Framework and the Generalised Historical Volatility Estimator," Monash Econometrics and Business Statistics Working Papers 10/98, Monash University, Department of Econometrics and Business Statistics.
  • Handle: RePEc:msh:ebswps:1998-10
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    References listed on IDEAS

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    1. Min, Chung-ki & Zellner, Arnold, 1993. "Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 89-118, March.
    2. Smith, Michael, 2000. "Modeling and Short-term Forecasting of New South Wales Electricity System Load," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 465-478, October.
    3. Chib, Siddhartha & Greenberg, Edward, 1995. "Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models," Journal of Econometrics, Elsevier, vol. 68(2), pages 339-360, August.
    4. Smith, Michael & Kohn, Robert, 1996. "Nonparametric regression using Bayesian variable selection," Journal of Econometrics, Elsevier, vol. 75(2), pages 317-343, December.
    5. Mandy, David M. & Martins-Filho, Carlos, 1993. "Seemingly unrelated regressions under additive heteroscedasticity : Theory and share equation applications," Journal of Econometrics, Elsevier, vol. 58(3), pages 315-346, August.
    6. Neil Shephard & Michael K Pitt, 1998. "Time Varying Covariances: A Factor Stochastic Volatility Approach (with discussion," Economics Series Working Papers 1998-W05, University of Oxford, Department of Economics.
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    Citations

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    Cited by:

    1. John W. Galbraith & Victoria Zinde-Walsh, 2000. "Properties of Estimates of Daily GARCH Parameters Based on Intra-Day Observations," Econometric Society World Congress 2000 Contributed Papers 1800, Econometric Society.
    2. Moosa, Imad A. & Bollen, Bernard, 2002. "A benchmark for measuring bias in estimated daily value at risk," International Review of Financial Analysis, Elsevier, vol. 11(1), pages 85-100.

    More about this item

    Keywords

    EVALUATION ; TIME SERIES ; FINANCIAL MARKET;

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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