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A Mixed Frequency Stochastic Volatility Model for Intraday Stock Market Returns

Author

Listed:
  • Jeremias Bekierman
  • Bastian Gribisch

Abstract

We propose a mixed frequency stochastic volatility model for intraday returns. To account for long-memory type of dependence patterns we introduce a long-run component that changes daily and a short-run component that captures the remaining intraday volatility dynamics. We analyze the model’s stochastic properties and extend it to capture leverage effects and overnight return information. The model is estimated by simulated maximum likelihood using efficient importance sampling. We apply the model to 30-min returns of 12 stocks. The results show that the model successfully accounts for the complex dynamic and distributional properties of asset returns both on the intraday and the daily frequency.

Suggested Citation

  • Jeremias Bekierman & Bastian Gribisch, 2021. "A Mixed Frequency Stochastic Volatility Model for Intraday Stock Market Returns," Journal of Financial Econometrics, Oxford University Press, vol. 19(3), pages 496-530.
    • Handle: RePEc:oup:jfinec:v:19:y:2021:i:3:p:496-530.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbz021
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    Citations

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    Cited by:

    1. Dette, Holger & Golosnoy, Vasyl & Kellermann, Janosch, 2022. "Correcting Intraday Periodicity Bias in Realized Volatility Measures," Econometrics and Statistics, Elsevier, vol. 23(C), pages 36-52.
    2. ChanKyu Paik & Jinhee Choi & Ivan Ureta Vaquero, 2024. "Algorithm-Based Low-Frequency Trading Using a Stochastic Oscillator, Williams%R, and Trading Volume for the S&P 500," JRFM, MDPI, vol. 17(11), pages 1-20, November.
    3. Holger Dette & Vasyl Golosnoy & Janosch Kellermann, 2023. "The effect of intraday periodicity on realized volatility measures," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(3), pages 315-342, April.
    4. Watanabe, Toshiaki & Nakajima, Jouchi, 2023. "High-frequency realized stochastic volatility model," Discussion paper series HIAS-E-127, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.

    More about this item

    Keywords

    intraday stochastic volatility; mixed frequency; overnight returns; leverage; efficient importance sampling;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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