Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility

Makoto Takahashi, Toshiaki Watanabe and Yasuhiro Omori

No HIAS-E-104, Discussion paper series from Hitotsubashi Institute for Advanced Study, Hitotsubashi University

Abstract: This paper compares the volatility predictive abilities of some time-varying volatility models such as thestochastic volatility (SV) and exponential GARCH (EGARCH) models using daily returns, the heterogeneous au-toregressive (HAR) model using daily realized volatility (RV) and the realized SV (RSV) and realized EGARCH(REGARCH) models using the both. The data are the daily return and RV of Dow Jones Industrial Aver-age (DJIA) in US and Nikkei 225 (N225) in Japan. All models are extended to accommodate the well-knownphenomenon in stock markets of a negative correlation between today's return and tomorrow's volatility. Weestimate the HAR model by the ordinary least squares (OLS) and the EGARCH and REGARCH models bythe quasi-maximum likelihood (QML) method. Since it is not straightforward to evaluate the likelihood of theSV and RSV models, we apply a Bayesian estimation via Markov chain Monte Carlo (MCMC) to them. Byconducting predictive ability tests and analyses based on model confidence sets, we confirm that the models us-ing RV outperform the models without RV, that is, the RV provides useful information on forecasting volatility.Moreover, we find that the realized SV model performs best and the HAR model can compete with it. Thecumulative loss analysis suggests that the differences of the predictive abilities among the models are partlycaused by the rise of volatility.

Keywords: Exponential GARCH (EGARCH) model; Heterogeneous autoregressive (HAR) model; Markov chain Monte Carlo (MCMC); Realized volatility; Stochastic volatility; Volatility forecasting (search for similar items in EconPapers)
JEL-codes: C11 C22 C53 C58 G17 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2021-01
New Economics Papers: this item is included in nep-cwa, nep-ets, nep-fmk, nep-for, nep-ore and nep-rmg
Note: January 4, 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:hit:hiasdp:hias-e-104

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