Time-varying distributions and the optimal hedge ratios for stock index futures

1995 ◽  
Vol 5 (3) ◽  
pp. 131-137 ◽  
Author(s):  
Tae H. Park ◽  
Lorne N. Switzer
Keyword(s):  
Stock Index ◽  
Stock Index Futures ◽  
Time Varying ◽  
Index Futures ◽  
Hedge Ratios ◽  
Optimal Hedge

Hedging and Optimal Hedge Ratios for International Index Futures Markets

2009 ◽  
Vol 12 (04) ◽  
pp. 593-610 ◽  
Author(s):  
Cheng-Few Lee ◽  
Kehluh Wang ◽  
Yan Long Chen
Keyword(s):  
Futures Markets ◽  
Minimum Variance ◽  
Stock Index ◽  
Stock Index Futures ◽  
Hedge Ratio ◽  
Index Futures ◽  
Static Hedging ◽  
Hedge Ratios ◽  
Optimal Hedge ◽  
Mean Variance

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.

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
Keyword(s):  
Least Square ◽  
Stock Index ◽  
Stock Index Futures ◽  
Vector Error Correction ◽  
Index Futures ◽  
Portfolio Returns ◽  
Hedging Effectiveness ◽  
Hedge Ratios ◽  
Out Of Sample ◽  
Optimal Hedge

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.

scholarly journals Hedge Ratios in South African Stock Index Futures

2010 ◽  
Vol 9 (3) ◽  
pp. 285-304 ◽  
Author(s):  
Stavros Degiannakis ◽  
Christos Floros
Keyword(s):  
South African ◽  
Stock Index ◽  
Stock Index Futures ◽  
Index Futures ◽  
Hedge Ratios

Time-varying jump risk premia in stock index futures returns

2011 ◽  
Vol 32 (7) ◽  
pp. 639-659 ◽  
Author(s):  
Wing Hong Chan ◽  
Liling Feng
Keyword(s):  
Risk Premia ◽  
Stock Index ◽  
Stock Index Futures ◽  
Time Varying ◽  
Jump Risk ◽  
Index Futures

Hedge ratios in Greek stock index futures market

2004 ◽  
Vol 14 (15) ◽  
pp. 1125-1136 ◽  
Author(s):  
Christos Floros * ◽  
Dimitrios V. Vougas
Keyword(s):  
Futures Market ◽  
Stock Index ◽  
Stock Index Futures ◽  
Index Futures ◽  
Hedge Ratios
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