scholarly journals The Hedging Effectiveness of Stock Index Futures: Evidence for the S&P CNX Nifty Index Traded in India

2011 ◽  
Vol 6 (1) ◽  
pp. 111-123 ◽  
Author(s):  
Kailash Pradhan

The Hedging Effectiveness of Stock Index Futures: Evidence for the S&P CNX Nifty Index Traded in IndiaThis study evaluates optimal hedge ratios and the hedging effectiveness of stock index futures. The optimal hedge ratios are estimated from the ordinary least square (OLS) regression model, the vector autoregression model (VAR), the vector error correction model (VECM) and multivariate generalized autoregressive conditional heteroskedasticity (M-GARCH) models such as VAR-GARCH and VEC-GARCH using the S&P CNX Nifty index and its futures index. Hedging effectiveness is measured in terms of within sample and out of sample risk-return trade-off at various forecasting horizons. The analysis found that the VEC-GARCH time varying hedge ratio provides the greatest portfolio risk reduction and generates the highest portfolio returns.

2009 ◽  
Vol 12 (04) ◽  
pp. 593-610 ◽  
Author(s):  
Cheng-Few Lee ◽  
Kehluh Wang ◽  
Yan Long Chen

This empirical study utilizes four static hedging models (OLS Minimum Variance Hedge Ratio, Mean-Variance Hedge Ratio, Sharpe Hedge Ratio, and MEG Hedge Ratio) and one dynamic hedging model (bivariate GARCH Minimum Variance Hedge Ratio) to find the optimal hedge ratios for Taiwan Stock Index Futures, S&P 500 Stock Index Futures, Nikkei 225 Stock Index Futures, Hang Seng Index Futures, Singapore Straits Times Index Futures, and Korean KOSPI 200 Index Futures. The effectiveness of these ratios is also evaluated. The results indicate that the methods of conducting optimal hedging in different markets are not identical. However, the empirical results confirm that stock index futures are effective direct hedging instruments, regardless of hedging schemes or hedging horizons.


2019 ◽  
Vol 118 (3) ◽  
pp. 137-152
Author(s):  
A. Shanthi ◽  
R. Thamilselvan

The major objective of the study is to examine the performance of optimal hedge ratio and hedging effectiveness in stock futures market in National Stock Exchange, India by estimating the following econometric models like Ordinary Least Square (OLS), Vector Error Correction Model (VECM) and time varying Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) model by evaluating in sample observation and out of sample observations for the period spanning from 1st January 2011 till 31st March 2018 by accommodating sixteen stock futures retrieved through www.nseindia.com by considering banking sector of Indian economy. The findings of the study indicate both the in sample and out of sample hedging performances suggest the various strategies obtained through the time varying optimal hedge ratio, which minimizes the conditional variance performs better than the employed alterative models for most of the underlying stock futures contracts in select banking sectors in India. Moreover, the study also envisage about the model selection criteria is most important for appropriate hedge ratio through risk averse investors. Finally, the research work is also in line with the previous attempts Myers (1991), Baillie and Myers (1991) and Park and Switzer (1995a, 1995b) made in the US markets


2010 ◽  
Vol 9 (3) ◽  
pp. 285-304 ◽  
Author(s):  
Stavros Degiannakis ◽  
Christos Floros

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