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High-frequency realized stochastic volatility model

Author

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  • Watanabe, Toshiaki
  • Nakajima, Jouchi

Abstract

A new high-frequency realized stochastic volatility model is proposed. Apart from the standard daily-frequency stochastic volatility model, the high-frequency stochastic volatility model is fit to intraday returns by extensively incorporating intraday volatility patterns. The daily realized volatility calculated using intraday returns is incorporated into the high-frequency stochastic volatility model by considering the bias in the daily realized volatility caused by microstructure noise. The volatility of intraday returns is assumed to consist of the autoregressive process, the seasonal component of the intraday volatility pattern, and the announcement component responding to macroeconomic announcements. A Bayesian method via Markov chain Monte Carlo is developed for the analysis of the proposed model. The empirical analysis using the 5-minute returns of E-mini S&P 500 futures provides evidence that our high-frequency realized stochastic volatility model improves in-sample model fit and volatility forecasting over the existing models.

Suggested Citation

  • Watanabe, Toshiaki & Nakajima, Jouchi, 2023. "High-frequency realized stochastic volatility model," Discussion paper series HIAS-E-127, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    • Handle: RePEc:hit:hiasdp:hias-e-127
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    File URL: https://hermes-ir.lib.hit-u.ac.jp/hermes/ir/re/78469/070_hiasDP-E-127.pdf
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    References listed on IDEAS

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    Cited by:

    1. Daichi Hiraki & Siddhartha Chib & Yasuhiro Omori, 2024. "Stochastic Volatility in Mean: Efficient Analysis by a Generalized Mixture Sampler," Papers 2404.13986, arXiv.org.

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    More about this item

    Keywords

    Bayesian analysis; High-frequency data; Markov chain Monte Carlo; Realized volatility; Stochastic volatility model; Volatility forecasting;
    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
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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