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An extension of stochastic volatility model with mixed frequency information

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  • Shang, Yuhuang
  • Liu, Lulu

Abstract

This paper extends the SV model to the MF-SV model with mixed frequency information. We show the small sample properties with Monte Carlo experiment with MCMC method. The MF-SV model outperforms the basic SV model in the in-sample performance.

Suggested Citation

  • Shang, Yuhuang & Liu, Lulu, 2017. "An extension of stochastic volatility model with mixed frequency information," Economics Letters, Elsevier, vol. 155(C), pages 144-148.
    • Handle: RePEc:eee:ecolet:v:155:y:2017:i:c:p:144-148
    DOI: 10.1016/j.econlet.2017.04.003
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    References listed on IDEAS

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    1. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    2. Nakajima, Jouchi & Omori, Yasuhiro, 2009. "Leverage, heavy-tails and correlated jumps in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2335-2353, April.
    3. Harvey, Andrew C & Shephard, Neil, 1996. "Estimation of an Asymmetric Stochastic Volatility Model for Asset Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 429-434, October.
    4. Ravi Bansal & Dana Kiku & Ivan Shaliastovich & Amir Yaron, 2014. "Volatility, the Macroeconomy, and Asset Prices," Journal of Finance, American Finance Association, vol. 69(6), pages 2471-2511, December.
    5. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    6. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
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    Cited by:

    1. Yang, Xinglin & Shang, Yuhuang, 2024. "Pricing VIX futures with mixed frequency macroeconomic information," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 847-857.
    2. Virbickaitė, Audronė & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian predictive distributions of oil returns using mixed data sampling volatility models," Resources Policy, Elsevier, vol. 86(PA).
    3. Shang, Yuhuang & Zheng, Tingguo, 2021. "Mixed-frequency SV model for stock volatility and macroeconomics," Economic Modelling, Elsevier, vol. 95(C), pages 462-472.

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    More about this item

    Keywords

    Stochastic volatility; Mixed-frequency; Monte Carlo experiment; MCMC method; Unobservable component;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G1 - Financial Economics - - General Financial Markets

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