Abstract
The hedging effectiveness for bank futures and CNX nifty are evaluated in this study. The study is based on 9,569 observations of the daily data for these index futures. For evaluation ordinary least square, co-integrated ordinary least square, generalized auto-regressive conditional heteroscedasticity (1, 1), and constant correlation generalized auto-regressive conditional heteroscedasticity (1, 1) hedging methods are estimated and compared. Result shows that constant correlation generalized auto-regressive conditional heteroscedasticity (1, 1) is an efficient hedging method that maximizes investors’ utility function considering transaction costs. Therefore, investors can rely on this constant correlation generalized auto-regressive conditional heteroscedasticity (1, 1) hedging method.
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