GARCH DIFFUSION MODEL, iVIX, AND VOLATILITY RISK PREMIUM

Xinyu Wu () and Hailin Zhou ()
Additional contact information
Xinyu Wu: School of Finance, Anhui University of Finance and Economics, China
Hailin Zhou: School of Finance, Anhui University of Finance and Economics, China

ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, 2016, vol. 50, issue 1, 327-342

Abstract: This paper investigates the volatility risk premium in the non-affine GARCH diffusion model of stochastic volatility using the Chinese Volatility Index (iVIX). Firstly, we derive the corresponding implied iVIX formula under the GARCH diffusion model. Then, using joint data on the Shanghai 50ETF and iVIX index, we develop an efficient importance sampling (EIS)-based joint maximum likelihood (ML) estimation method for the objective and risk-neutral parameters of the GARCH diffusion model. Furthermore, a particle filter-based estimation method is developed for extracting the latent volatility. Finally, we apply our proposed approach to the actual data on the Shanghai 50ETF and iVIX index. Empirical results show that the volatility risk is priced by the market, and the volatility risk premium is negative, implying that investors act risk averse in the Shanghai stock market.

Keywords: GARCH diffusion model; iVIX; volatility risk premium; efficient importance sampling; particle filter. (search for similar items in EconPapers)
JEL-codes: C13 C32 C58 G13 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
ftp://www.eadr.ro/RePEc/cys/ecocyb_pdf/ecocyb1_2016p327-342.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cys:ecocyb:v:50:y:2016:i:1:p:327-342

Access Statistics for this article

ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH is currently edited by Gheorghe RUXANDA

More articles in ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH from Faculty of Economic Cybernetics, Statistics and Informatics Contact information at EDIRC.
Bibliographic data for series maintained by Corina Saman ().