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Hedging Effectiveness of Constant and Time-Varying Hedge Ratio in Indian Commodity Futures Markets: Evidence from the Multi-Commodity Exchange

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  • P Srinivasan

Abstract

The present study examines the performance of various hedge ratios estimated under different econometric models, viz., the conventional OLS model, the VECM, and the Multivariate-GARCH (M-GARCH) with error correction model, and compares them in terms of variance minimization criterion over the in-sample and out-of-sample periods for the selected commodity market indices of Multi-Commodity Exchange (MCX), viz., MCXCOMDEX, MCXAGRI, MCXENERGY, and MCXMETAL. The data span of the study is from June 8, 2005 to September 31, 2010. Out of the total observations of the respective commodity market indices, the last 60 observations were used to facilitate out-of-sample hedge ratio performance comparison. By and large, the comparison of both in-sample and out-of-sample hedging performances in the present study indicates that the hedging strategy obtained from time-varying hedge ratio, which minimizes the conditional variance, performs better than the alternative models for all commodity market indices, except MCXAGRI. This implies that in selecting the most appropriate hedge ratio, the investor’s degree of risk aversion might play a relatively important role. This suggests that risk aversion being the major goal of an investor, the dynamic M-GARCH model hedging strategy performs best in reducing the conditional variance of the hedged portfolio.

Suggested Citation

  • P Srinivasan, 2011. "Hedging Effectiveness of Constant and Time-Varying Hedge Ratio in Indian Commodity Futures Markets: Evidence from the Multi-Commodity Exchange," The IUP Journal of Financial Economics, IUP Publications, vol. 0(3), pages 7-27, September.
  • Handle: RePEc:icf:icfjfe:v:09:y:2011:i:3:p:7-27
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    1. Regmund, Wes & Robinson, John & Anderson, David, "undated". "Higher and More Stable Returns From Cottonseed," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252813, Southern Agricultural Economics Association.

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