Delta Hedging and Volatility-Price Elasticity: A Two-Step Approach

42 Pages Posted: 24 Nov 2020

See all articles by Peng Zhu

Peng Zhu

Nanjing University

Kun Xia

Hong Kong University of Science & Technology (HKUST) - HKUST Business School

Xuewei Yang

Nanjing University - School of Management and Engineering

Date Written: October 8, 2020

Abstract

Traditional Black-Scholes delta do not minimize variance of hedging risk since there exists a long run negative relationship between implied volatility and underlying price. This paper presents a two-step empirical approach of option delta hedging in which the hedging ratio is determined by volatility-price relationship. Specifically, we find that the dependency of minimum variance (MV) hedging ratio on volatility-price elasticity is quite stable and that the volatility-price elasticity exhibits characteristic of mean-reverting. Therefore we first estimate a model which can capture the dependency of hedging ratio on volatility-price elasticity, and then substitute predictions of future volatility-price elasticity into the pre-fixed model to obtain the MV hedging ratio. We test the new approach using the S&P 500 daily option data and show that our approach results in higher hedging gain than related methods appeared in recent works.

Keywords: Option; Delta hedging; Dynamic of volatility-price elasticity; Risk management; Minimum variance

JEL Classification: G13

Suggested Citation

Zhu, Peng and Xia, Kun and Yang, Xuewei, Delta Hedging and Volatility-Price Elasticity: A Two-Step Approach (October 8, 2020). Available at SSRN: https://ssrn.com/abstract=3707369 or http://dx.doi.org/10.2139/ssrn.3707369

Peng Zhu

Nanjing University ( email )

Nanjing, Jiangsu 210093
China

Kun Xia

Hong Kong University of Science & Technology (HKUST) - HKUST Business School ( email )

Clearwater Bay
Kowloon, 999999
Hong Kong

Xuewei Yang (Contact Author)

Nanjing University - School of Management and Engineering ( email )

22 Hankou Road, Gulou District
Nanjing, Jiangsu 210093
China

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