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Estimation of Hedging Effectiveness Using Variance Reduction and Risk-Return Approaches: Evidence from National Stock Exchange of India

International Journal of Business Analytics and Intelligence

Volume 6 Issue 1

Published: 2018
Author(s) Name: Mandeep Kaur, Kapil Gupta | Author(s) Affiliation: Research Scholar, Dept. of Management, I. K. Gujral Punjab Technical University, Kapurthala, Punjab.
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Present study estimates the hedging effectiveness by applying variance-reduction framework and risk-return framework using near month contracts of three benchmark indices (NIFTY50, NIFTYIT, and BANKNIFTY) traded at National Stock Exchange of India (NSE) for the sample period from June 2000 to March 31, 2017 by using nine optimal hedge ratio models. Out of these nine models, six are constant hedging models and three are time-varying hedging models. The study finds that using variance-reduction framework, highest hedging effectiveness is achieved using Ordinary Least Square model; whereas, 1:1 naïve hedge ratio gives lowest hedging effectiveness. On the other hand, when hedging effectiveness is estimated in a risk-return framework, naïve hedge ratio gives highest hedging effectiveness; whereas, OLS gives the least estimate. Secondly, the coefficients of both optimal hedge ratio as well as hedging effectiveness have increased during post-crisis period implying an increase in the cost of hedging. These findings suggests that conventional hedging models are more efficient than highly complicated time-varying hedging models for estimating optimal hedge ratio, these findings are consistent with the findings of Lien (2005), Bhaduri and Durai (2007), Bhargava (2007), Mandal (2011), Wang et al. (2015).

Keywords: Hedging Effectiveness, Optimal Hedge Ratio, Equity Futures Market, Generalized Auto-regressive Conditional Heteroscedasticity (GARCH), Constant Hedge Ratio, Time-Varying Hedge Ratio

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