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HARK the SHARK: Realized Volatility Modeling with Measurement Errors and Nonlinear Dependencies

Author

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  • Giuseppe Buccheri
  • Fulvio Corsi

Abstract

Despite their effectiveness, linear models for realized variance neglect measurement errors on integrated variance and exhibit several forms of misspecification due to the inherent nonlinear dynamics of volatility. We propose new extensions of the popular approximate long-memory heterogeneous autoregressive (HAR) model apt to disentangle these effects and quantify their separate impact on volatility forecasts. By combining the asymptotic theory of the realized variance estimator with the Kalman filter and by introducing time-varying HAR parameters, we build new models that account for: (i) measurement errors (HARK), (ii) nonlinear dependencies (SHAR) and (iii) both measurement errors and nonlinearities (SHARK). The proposed models are simply estimated through standard maximum likelihood methods and are shown, both on simulated and real data, to provide better out-of-sample forecasts compared to standard HAR specifications and other competing approaches.

Suggested Citation

  • Giuseppe Buccheri & Fulvio Corsi, 2021. "HARK the SHARK: Realized Volatility Modeling with Measurement Errors and Nonlinear Dependencies," Journal of Financial Econometrics, Oxford University Press, vol. 19(4), pages 614-649.
    • Handle: RePEc:oup:jfinec:v:19:y:2021:i:4:p:614-649.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbz025
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    Citations

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    Cited by:

    1. Li, Chenxing & Zhang, Zehua & Zhao, Ran, 2023. "Volatility or higher moments: Which is more important in return density forecasts of stochastic volatility model?," MPRA Paper 118459, University Library of Munich, Germany.
    2. Christensen, Bent Jesper & Kjær, Mads Markvart & Veliyev, Bezirgen, 2023. "The incremental information in the yield curve about future interest rate risk," Journal of Banking & Finance, Elsevier, vol. 155(C).
    3. Hiroyuki Kawakatsu, 2022. "Modeling Realized Variance with Realized Quarticity," Stats, MDPI, vol. 5(3), pages 1-25, September.

    More about this item

    Keywords

    realized volatility; HAR; measurement errors; nonlinear time series; score-driven models; Kalman filter;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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