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Estimation of Generalized Realized Stochastic Volatility Model: An Application to Calendar Effect of Nikkei 225

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  • Ishihara, Tsunehiro

Abstract

A stochastic volatility model with realized measures of volatility (Realized Stochastic Volatility model, RSV model) is extended. The regression structures, correlations between returns and realized measurement errors, and multiple realized measures are incorporated into the model. A Bayesian estimation method using the Markov chain Monte Carlo method which is called the mixture sampler is proposed for the generalized realized RSV models. The realized volatility models in the previous studies are surveyed and relation them and our models is discussed. The proposed models and estimation methods are applied for the Nikkei 225 daily closing price returns and realized volatility measures. The calendar effects of latent and realized volatilities are estimated separately. Different behaviors are found for them in the day-of-the-week effect., A stochastic volatility model with realized measures of volatility (Realized Stochastic Volatility model, RSV model) is extended. The regression structures, correlations between returns and realized measurement errors, and multiple realized measures are incorporated into the model. A Bayesian estimation method using the Markov chain Monte Carlo method which is called the mixture sampler is proposed for the generalized realized RSV models. The realized volatility models in the previous studies are surveyed and relation them and our models is discussed. The proposed models and estimation methods are applied for the Nikkei 225 daily closing price returns and realized volatility measures. The calendar effects of latent and realized volatilities are estimated separately. Different behaviors are found for them in the day-of-the-week effect.

Suggested Citation

  • Ishihara, Tsunehiro, 2015. "Estimation of Generalized Realized Stochastic Volatility Model: An Application to Calendar Effect of Nikkei 225," Economic Review, Hitotsubashi University, vol. 66(1), pages 1-18, January.
    • Handle: RePEc:hit:ecorev:v:66:y:2015:i:1:p:1-18
    DOI: 10.15057/27507
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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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