Academic Journal
Bayesian analysis of intraday stochastic volatility models of high-frequency stock returns with skew heavy-tailed errors
| العنوان: | Bayesian analysis of intraday stochastic volatility models of high-frequency stock returns with skew heavy-tailed errors |
|---|---|
| المؤلفون: | Nakakita, Makoto, Nakatsuma, Teruo |
| بيانات النشر: | MDPI |
| سنة النشر: | 2021 |
| المجموعة: | EconStor (German National Library of Economics, ZBW) |
| مصطلحات موضوعية: | ddc:330, Bayesian inference, high-frequency financial time series, intraday seasonality, Markov chain Monte Carlo, stochastic volatility |
| الوصف: | 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. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 1911-8074 |
| Relation: | gbv-ppn:1759773085; Journal: Journal of Risk and Financial Management; Volume: 14; Year: 2021; Issue: 4; Pages: 1-29; Basel: MDPI; http://hdl.handle.net/10419/239561 |
| DOI: | 10.3390/jrfm14040145 |
| الاتاحة: | http://hdl.handle.net/10419/239561 https://doi.org/10.3390/jrfm14040145 |
| Rights: | https://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: | edsbas.262D70BC |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 19118074 |
|---|---|
| DOI: | 10.3390/jrfm14040145 |