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Realized volatility: a review

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Author Info
Michael McAleer (University of Western Australia)
Marcelo Cunha Medeiros () (Department of Economics PUC-Rio)

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Abstract

This paper reviews the exciting and rapidly expanding literature on realized volatility. After presenting a general univariate framework for estimating realized volatilities, a simple discrete time model is presented in order to motivate the main results. A continuous time specification provides the theoretical foundation for the main results in this literature. Cases with and without microstructure noise are considered, and it is shown how microstructure noise can cause severe problems in terms of consistent estimation of the daily realized volatility. Independent and dependent noise processes are examined. The most important methods for providing consistent estimators are presented, and a critical exposition of different techniques is given. The finite sample properties are discussed in comparison with their asymptotic properties. A multivariate model is presented to discuss estimation of the realized covariances. Various issues relating to modelling and forecasting realized volatilities are considered. The main empirical findings using univariate and multivariate methods are summarized.

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Paper provided by Department of Economics PUC-Rio (Brazil) in its series Textos para discussão with number 531 Publication status: Forthcoming in Econometric Reviews.

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Length: 56p
Date of creation: Nov 2006
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Handle: RePEc:rio:texdis:531

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Gregory H. Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility
    ," Working Papers 07-20, Bank of Canada. [Downloadable!]
  2. M. Angeles Carnero, 2004. "Persistence and Kurtosis in GARCH and Stochastic Volatility Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 319-342. [Downloadable!] (restricted)
  3. Siem Jan Koopman & Borus Jungbacker & Eugenie Hol, 2004. "Forecasting Daily Variability of the S&P 100 Stock Index using Historical, Realised and Implied Volatility Measurements," Tinbergen Institute Discussion Papers 04-016/4, Tinbergen Institute. [Downloadable!]
    Other versions:
  4. Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics. [Downloadable!]
    Other versions:
  5. Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121. [Downloadable!] (restricted)
  6. Oomen, Roel C.A., 2006. "Properties of Realized Variance Under Alternative Sampling Schemes," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 219-237, April. [Downloadable!] (restricted)
  7. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(01), pages 232-261, February. [Downloadable!]
  8. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility," CIRJE F-Series CIRJE-F-488, CIRJE, Faculty of Economics, University of Tokyo. [Downloadable!]
  9. Peter Reinhard Hansen & Asger Lunde, 2005. "A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 525-554. [Downloadable!] (restricted)
  10. Asger Lunde & Esben Hoeg, 2003. "Wavelet Estimation of Integrated Volatility," Computing in Economics and Finance 2003 274, Society for Computational Economics. [Downloadable!]
  11. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March. [Downloadable!] (restricted)
  12. Valeri Voev & Asger Lunde, 2007. "Integrated Covariance Estimation using High-frequency Data in the Presence of Noise," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 68-104. [Downloadable!] (restricted)
  13. MArcelo Carvalho & MArco Aurelio Freire & Marcelo Cunha Medeiros & Leonardo Souza, 2006. "Modeling and forecasting the volatility of Brazilian asset returns," Textos para discussão 530, Department of Economics PUC-Rio (Brazil). [Downloadable!]
  14. Martin Martens & Dick van Dijk & Michiel de Pooter, 2004. "Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity," Tinbergen Institute Discussion Papers 04-067/4, Tinbergen Institute. [Downloadable!]
  15. Jeremy Large, 2005. "Estimating quadratic variation when quoted prices jump by a constant increment," Economics Papers 2005-W05, Economics Group, Nuffield College, University of Oxford. [Downloadable!]
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  16. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Power Variation and Time Change," Economics Papers 2002-W24, Economics Group, Nuffield College, University of Oxford. [Downloadable!]
  17. McKensie, C.R. & McAleer, M., 1990. "On Efficient Estimation and Correct Inference in Models with Generated Regressions: A General Approach," Papers 211, Australian National University - Department of Economics.
  18. Rohit Deo & Clifford Hurvich & Yi Lu, 2005. "Forecasting Realized Volatility Using a Long Memory Stochastic Volatility Model: Estimation, Prediction and Seasonal Adjustment," Econometrics 0501002, EconWPA. [Downloadable!]
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  19. Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 2003. "The economic value of volatility timing using "realized" volatility," Journal of Financial Economics, Elsevier, vol. 67(3), pages 473-509, March. [Downloadable!] (restricted)
  20. Neil Shephard & Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Series Working Papers 264, University of Oxford, Department of Economics. [Downloadable!]
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  21. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April. [Downloadable!] (restricted)
  22. Biais, Bruno & Glosten, Larry & Spatt, Chester, 2005. "Market microstructure: A survey of microfoundations, empirical results, and policy implications," Journal of Financial Markets, Elsevier, vol. 8(2), pages 217-264, May. [Downloadable!] (restricted)
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  23. Jeff Fleming, 2001. "The Economic Value of Volatility Timing," Journal of Finance, American Finance Association, vol. 56(1), pages 329-352, 02. [Downloadable!] (restricted)
  24. Roel C. A. Oomen, 2005. "Properties of Bias-Corrected Realized Variance Under Alternative Sampling Schemes," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 555-577. [Downloadable!] (restricted)
  25. Peter Hansen & Jeremy Large & Asger Lunde, 2008. "Moving Average-Based Estimators of Integrated Variance," Econometric Reviews, Taylor and Francis Journals, vol. 27(1-3), pages 79-111. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Makoto Takahashi & Yasuhiro Omori & Toshiaki Watanabe, 2007. "Estimating Stochastic Volatility Models Using Daily Returns and Realized Volatility Simultaneously," CIRJE F-Series CIRJE-F-515, CIRJE, Faculty of Economics, University of Tokyo. [Downloadable!]
  2. Marcel Scharth & Marcelo Cunha Medeiros, 2006. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," Textos para discussão 532, Department of Economics PUC-Rio (Brazil). [Downloadable!]
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