Estimation of Hedging Effectiveness Using Variance Reduction and Risk-Return Approaches: Evidence from National Stock Exchange of India Mandeep Kaur*, Kapil Gupta** * Research Scholar, Department of Management, I. K. Gujral Punjab Technical University, Kapurthala, Punjab, India. Email: kaur_mandeep13@ymail.com ** Assistant Professor, Department of Management, I. K. Gujral Punjab Technical University, Kapurthala, Punjab, India. Email: kapilfutures@gmail.com Abstract 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 JEL: C13, C22, C32, D81, D82, G12, G14, N25, and O16 Introducton The globalization of fnancial markets as well as political and economic disturbances around the world have increased the exposure to fnancial risk. Therefore, as a need to hedge the fnancial risk, derivative contracts have been introduced which includes futures contracts, options contracts, swaps, swaptions, and so on. Literature observes that although futures market plays a signifcant role in hedging price risk, price discovery and increasing cash market effciency, yet hedging is considered the primary function of futures market. The co-movement and long-term equilibrium relationship between spot and futures market enables hedger to offset price fuctuations in underlying asset prices by taking opposite position in both spot and futures market. However, numerous studies 1 document the fact that such a relationship gets disturbed in the shortrun due to the presence of market frictions such as: noise trading, infrequent trading of component stocks of underlying index, difference in the trading cost in both the markets, violation of assumptions of cost of carry model, etc. Such disturbances lead to basis risk, which mandates a hedger to estimate the required number of futures contracts to achieve superior hedging effectiveness (according to specifc objective function to be optimized). While designing an effcient hedge strategy, the objective of investors to hedge is of prime consideration. There are three different views on hedging based upon investor’s objective to hedge. The traditional theory assumes 1 Castelino (1992); Figlewski (1984); Stoll and Whaley (1990) International Journal of Business Analytics and Intelligence 6 (1) 2018, 35-46 http://publishingindia.com/ijbai/