Are There Gains from Using Information over the Surface of Implied Volatilities?

Journal of Futures Markets (2017)

54 Pages Posted: 8 Apr 2016 Last revised: 15 Jan 2018

See all articles by Biao Guo

Biao Guo

Renmin University of China

Qian Han

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE)

Hai Lin

Victoria University of Wellington - School of Economics & Finance

Date Written: December 20, 2017

Abstract

We investigate the out-of-sample predictability of implied volatility using the information over the implied volatility surface. We show that implied volatility surface is useful for the out-of -sample forecast of implied volatility up to one week ahead. Trading strategies based on the predictability of implied volatility could generate significant risk-adjusted gains after controlling for transaction costs. Significant results also depend on the way of modelling implied volatility surface. We then calibrate a two-factor stochastic volatility option pricing model to implied volatility data. Results show that implied volatility is better explained by both long-term and short-term variance factors.

Keywords: implied volatility; price discovery; two-factor stochastic volatility model; out-of-sample forecast; economic significance

JEL Classification: G13; G14; G17

Suggested Citation

Guo, Biao and Han, Qian and Lin, Hai, Are There Gains from Using Information over the Surface of Implied Volatilities? (December 20, 2017). Journal of Futures Markets (2017). Available at SSRN: https://ssrn.com/abstract=2759812 or http://dx.doi.org/10.2139/ssrn.2759812

Biao Guo

Renmin University of China ( email )

Room B906
Xianjin Building
Beijing, Beijing 100872
China

Qian Han

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE) ( email )

A 307, Economics Building
Xiamen, Fujian 361005
China

HOME PAGE: http://www.wise.xmu.edu.cn/viewNews.asp?id=2422

Hai Lin (Contact Author)

Victoria University of Wellington - School of Economics & Finance ( email )

P.O. Box 600
Wellington 6001
New Zealand

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