Bayesian Analysis of Intraday Stochastic Volatility Models of High-Frequency Stock Returns with Skew Heavy-Tailed Errors
| Autor: | Teruo Nakatsuma, Makoto Nakakita |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Bayesian inference
lcsh:Risk in industry. Risk management 01 natural sciences 010104 statistics & probability symbols.namesake 0502 economics and business lcsh:Finance lcsh:HG1-9999 ddc:330 Econometrics 0101 mathematics stochastic volatility 050205 econometrics Mathematics Volatility clustering Stochastic volatility Model selection 05 social sciences Markov chain Monte Carlo high-frequency financial time series lcsh:HD61 intraday seasonality Skewness symbols Kurtosis Gibbs sampling |
| Zdroj: | Journal of Risk and Financial Management, Vol 14, Iss 145, p 145 (2021) Journal of Risk and Financial Management Volume 14 Issue 4 |
| ISSN: | 1911-8066 1911-8074 |
| Popis: | Intraday high-frequency data of stock returns exhibit not only typical characteristics (e.g., volatility clustering and the leverage effect) but also a cyclical pattern of return volatility that is known as intraday seasonality. In this paper, we extend the stochastic volatility (SV) model for application with such intraday high-frequency data and develop an efficient Markov chain Monte Carlo (MCMC) sampling algorithm for Bayesian inference of the proposed model. Our modeling strategy is two-fold. First, we model the intraday seasonality of return volatility as a Bernstein polynomial and estimate it along with the stochastic volatility simultaneously. Second, we incorporate skewness and excess kurtosis of stock returns into the SV model by assuming that the error term follows a family of generalized hyperbolic distributions, including variance-gamma and Student’s t distributions. To improve efficiency of MCMC implementation, we apply an ancillarity-sufficiency interweaving strategy (ASIS) and generalized Gibbs sampling. As a demonstration of our new method, we estimate intraday SV models with 1 min return data of a stock price index (TOPIX) and conduct model selection among various specifications with the widely applicable information criterion (WAIC). The result shows that the SV model with the skew variance-gamma error is the best among the candidates. |
| Databáze: | OpenAIRE |
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