scholarly journals The Hedging Effectiveness and the Stability of the Optimal Hedge Ratios: Evidence for the Istanbul Stock Exchange 30 Contract

Pressacademia ◽  
2015 ◽  
Vol 4 (3) ◽  
pp. 351-351
Author(s):  
Hakan Er
Keyword(s):  
Stock Exchange ◽  
Hedging Effectiveness ◽  
Hedge Ratios ◽  
Istanbul Stock Exchange ◽  
The Stability ◽  
Optimal Hedge

Optimal Hedge Ratio and Hedging Effectiveness in Stock Futures Market: Evidence from National Stock Exchange, India

2019 ◽  
Vol 118 (3) ◽  
pp. 137-152
Author(s):  
A. Shanthi ◽  
R. Thamilselvan
Keyword(s):  
Banking Sector ◽  
Stock Exchange ◽  
Research Work ◽  
Futures Market ◽  
Least Square ◽  
Time Varying ◽  
Hedge Ratio ◽  
Hedging Effectiveness ◽  
Out Of Sample ◽  
Optimal Hedge

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

Examining the Hedging Effectiveness of Futures Contracts over Pre and Post Financial Crisis Period: Evidence from National Stock Exchange of India

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Kapil Gupta ◽  
Mandeep Kaur
Keyword(s):  
Financial Crisis ◽  
Stock Exchange ◽  
Futures Contracts ◽  
Price Risk ◽  
Hedge Ratio ◽  
Crisis Period ◽  
Hedging Effectiveness ◽  
Hedge Ratios ◽  
Time Invariant

Present study examines the efficiency of futures contracts in hedging unwanted price risk over highly volatile period i.e. June 2000 - December 2007 and January 2008 – June 2014, pre and post-financial crisis period, by using S&PC NXNIFTY, CNXIT and BANKNIFTY for near month futures contracts. The hedge ratios have been estimated by using five methods namely Ederingtons Model, ARMA-OLS, GARCH (p,q), EGARCH (p,q) and TGARCH (p,q). The study finds that hedging effectiveness increased during post crisis period for S&PC NXNIFTY and BANKNIFTY. However, for CNXIT hedging effectiveness was better during pre-crisis period than post crisis. The study also finds that time-invariant hedge ratio is more efficient than time-variant hedge ratio.

scholarly journals Optimal Hedging Strategies for Natural Gas

2020 ◽  
Vol 12 (8) ◽  
pp. 1
Author(s):  
Changfeng Zhou ◽  
Huan Cai
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Financial Risk ◽  
Natural Gas Market ◽  
Hedging Strategies ◽  
Hedging Effectiveness ◽  
Hedge Ratios ◽  
Asset Portfolio ◽  
Gas Market ◽  
Optimal Hedge

This study examines the optimal hedge performance between natural gas market and crude oil, ECO, gold and US-bonds markets. To calculate optimal hedge ratios and hedging effectiveness, we apply several multivariate volatility models, namely CCC, DCC, cDCC and bayesDCC. The empirical results show that crude oil is the best asset to hedge natural gas followed by gold and ECO. This is a new result relative to the existing literature on natural gas prices. Additionally, we find that the bayesDCC model has the best performance on optimal hedge ratios (OHRs) calculation in terms of hedging effectiveness. Our findings will hold important financial risk management implications and asset portfolio for those invest in natural gas market.

HEDGING EFFECTIVENESS OF CROSS-LISTED NIFTY INDEX FUTURES

2019 ◽  
Vol 19 (02) ◽  
pp. 1950011
Author(s):  
K. KIRAN KUMAR ◽  
SHREYA BOSE
Keyword(s):  
Variance Reduction ◽  
Stock Exchange ◽  
Conditional Correlation ◽  
Index Futures ◽  
Hedging Strategies ◽  
Hedging Effectiveness ◽  
Maximum Variance ◽  
Daily Data ◽  
Hedge Ratios ◽  
Autoregressive Conditional Heteroscedasticity

This paper investigates the hedging effectiveness of cross-listed Nifty Index futures and compares the performance of constant and dynamic optimal hedging strategies. We use daily data of Nifty index traded on the National Stock Exchange (NSE), India and cross-listed Nifty futures traded on the Singapore Stock Exchange (SGX) for a period of six years from July 15, 2010 to July 15, 2016. Various competing forms of Multivariate Generalised Autoregressive Conditional Heteroscedasticity (MGARCH) models, such as Constant Conditional Correlation (CCC) and Dynamic Conditional Correlation (DCC), have been employed to capture the time-varying volatility. The results clearly depict that dynamic hedge ratios outperform traditional constant hedge ratios with the DCC–GARCH model being the most efficient with maximum variance reduction from the unhedged portfolio.

Estimating Optimal Hedge Ratio and Hedging Effectiveness in the NSE Index Futures

2017 ◽  
Vol 6 (2) ◽  
pp. 108-131 ◽  
Author(s):  
Gurmeet Singh
Keyword(s):  
Stock Exchange ◽  
Futures Market ◽  
Minimum Variance ◽  
Econometric Models ◽  
Sample Period ◽  
Hedge Ratio ◽  
Index Futures ◽  
Hedging Effectiveness ◽  
Egarch Model ◽  
Optimal Hedge

This study attempts to study and suggest an optimal hedge ratio to Indian investors and traders by examining the three main indices of National Stock Exchange of India (NSE), namely, NIFTY, Bank NIFTY, and IT NIFTY, over the sample period from January 2011 to December 2015. The present study estimated the hedge ratio through six econometric models, namely, OLS, GARCH, EGARCH, TARCH, VAR, and VECM, in the minimum variance hedge ratio framework as suggested by Ederington (1979). The findings of the present study confirm the theoretical properties of Indian cash and futures market and suggest that the optimal hedge ratio estimated through EGARCH model was lowest for the NIFTY and Bank NIFTY, and that for IT NIFTY, the OLS model shows the lowest optimal hedge ratio as compared to that estimated through other models.

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.

Istanbul Stock Exchange

1994 ◽  
Vol 30 (3) ◽  
pp. 133-137
Author(s):  
Bahsayis Temir
Keyword(s):  
Stock Exchange ◽  
Istanbul Stock Exchange
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