Hedge ratio estimation and hedging effectiveness: the case of the S&P 500 stock index futures contract

This paper investigates the hedging effectiveness of the Standard & Poor’s (S&P) 500 stock index futures contract using weekly settlement prices for the period July 3rd, 1992 to June 30th, 2002. Particularly, it focuses on three areas of interest: the determination of the appropriate model for estimating a hedge ratio that minimizes the variance of returns; the hedging effectiveness and the stability of optimal hedge ratios through time; an in-sample forecasting analysis in order to examine the hedging performance of different econometric methods. The hedging performance of this contract is examined considering alternative methods, both constant and time-varying, for computing more effective hedge ratios. The results suggest the optimal hedge ratio that incorporates nonstationarity, long run equilibrium relationship and short run dynamics is reliable and useful for hedgers. Comparisons of the hedging effectiveness and in-sample hedging performance of each model imply that the error correction model (ECM) is superior to the other models employed in terms of risk reduction. Finally, the results for testing the stability of the optimal hedge ratio obtained from the ECM suggest that it remains stable over time.Hedging effectiveness; minimum variance hedge ratio (MVHR); hedging models; Standard & Poor’s 500 stock index futures

Optimal hedge ratio and the hedging performance of commodity futures: the case of Malaysian crude palm oil futures market

This paper aims to examine the hedging performance of the crude palm Oil futures Market in Malaysia. The optimal hedge ratios and the hedging performance are examined for two different futures contracts denoted as futures 1 and futures 2 using daily settlement prices from January 4, 2010 to October 31, 2017. Four econometric models comprising of the standard ordinary least square (OLS), vector auto-regression (VAR), vector error correction model (VECM) and the bivariate generalized autoregressive conditional heteroscedasticity (BGARCH) models are employed to compute hedge ratios. The first three models estimate constant hedge ratios while the last model estimates time varying hedge ratio. The effectiveness of the hedge ratios for two contracts is evaluated in terms of in-sample and out-of-sample performance. For in-sample performance, January 4, 2010 to October 31, 2016 period is used while for out-of-sample validation, a one year data from November 2016 to October 31, 2017 is used. The empirical results show that the bivariate GARCH model performs better in the reduction of risk for both periods and the nearest futures contract (next one month contract) appears to be better in hedging than the far futures contract (next two month contracts). This suggests that the investors can use crude palm oil futures contract particularly the nearest futures contract as an effective instrument to hedge the risk and the bivariate BEKK-GARCH as an efficient model for designing hedging strategy

Mutual fund performance in Slovenia : an analysis of mutual funds with investment policies in Europe and the energy sector

This paper examines the risk and return performance of mutual funds in Slovenia from 2005 until August 2009. The research is limited to the regional investment policies in Europe and the energy sector. Using monthly returns, we analyzed different risk-adjusted measures such as: the Treynor ratio, the Sortino ratio and the Information ratio. We also studied selections and timing ability using the Treynor-Mazuy model. The risk and return performance of mutual funds in the Slovenian market does not deviate from those in developed markets. We also found out that the selection ability of fund managers is better than market timing and that the findings of this paper are in accordance with other international studies

ESTIMATING HEDGING EFFECTIVENESS USING VARIANCE REDUCTION AND RISK-RETURN APPROACHES: EVIDENCE FROM NATIONAL STOCK EXCHANGE OF INDIA

The present study examines hedging effectiveness of futures contracts in India by using variance reduction approach and risk-return approach by applying eight econometric models. It is observed that OLS hedge ratio generates highest hedging effectiveness using variance reduction approach, whereas Naïve hedge ratio generates highest hedging effectiveness using risk-return approach. Overall, it is observed that time-invariant hedging model generates superior hedging effectiveness as compared to time-variant hedging model

Hedging efficiency of Atlantic salmon futures

This is an Accepted Manuscript of an article published by Taylor & Francis in AQUACULTURE ECONOMICS & MANAGEMENT on 24 Aug 2016, available online: http://dx.doi.org/10.1080/13657305.2016.1212123This article examines the hedging properties of Atlantic salmon futures. Hedging is important because it allows for mitigation of the risk of adverse price changes in the spot market. We examine the hedging efficiency of three types of hedging strategies; unhedged, fully hedged and hedging using optimal hedging ratios. To find the optimal hedge ratio we use an estimated constant hedge ratio, optimal hedge ratios estimated with rolling 20-week and 52-week windows, and bivariate GARCH models. The results provide evidence that hedging using futures contracts listed on Fish Pool reduces risk for producers of farmed Atlantic salmon. The best hedging efficiency is achieved with a simple one-to-one hedge, closely followed by the bivariate GARCH approach.acceptedVersio

The optimal hedge ratio and hedging effectiveness of stock index futures An empirical study of TAIEX index futures contract

Throughout research literature on hedging with futures, a number of techniques to estimate the optimal hedge ratio that minimizes volatility of the hedged portfolio returns have been proposed. While these techniques hold theoretical appeal, there has not consistent evidence of which the most appropriate hedging technique is. This study, using the futures contract on the Taiwan’s TAIEX total returns index, provides an empirical comparison of three different econometric techniques. Specifically, the conventional OLS regression model, the VECM, and the bivariate DCC-GARCH model are estimated, performance of which are compared among each other and with the naïve hedge to determine the best hedging strategy. Hedging effectiveness is evaluated in terms of in-sample and out-of-sample returns variance minimization, under three short-term hedging horizons. This study concludes that despite simplicity in estimation, the constant hedge ratio estimated by the OLS regression is the most reliable and effective hedging strategy for TAIEX index short-term investors. Nevertheless, under the highly volatile market condition experienced during the global financial crisis 2008-2009, a dynamic hedging strategy is favored

The optimal hedge ratio and hedging effectiveness of stock index futures An empirical study of TAIEX index futures contract

Throughout research literature on hedging with futures, a number of techniques to estimate the optimal hedge ratio that minimizes volatility of the hedged portfolio returns have been proposed. While these techniques hold theoretical appeal, there has not consistent evidence of which the most appropriate hedging technique is. This study, using the futures contract on the Taiwan’s TAIEX total returns index, provides an empirical comparison of three different econometric techniques. Specifically, the conventional OLS regression model, the VECM, and the bivariate DCC-GARCH model are estimated, performance of which are compared among each other and with the naïve hedge to determine the best hedging strategy. Hedging effectiveness is evaluated in terms of in-sample and out-of-sample returns variance minimization, under three short-term hedging horizons. This study concludes that despite simplicity in estimation, the constant hedge ratio estimated by the OLS regression is the most reliable and effective hedging strategy for TAIEX index short-term investors. Nevertheless, under the highly volatile market condition experienced during the global financial crisis 2008-2009, a dynamic hedging strategy is favored

Investigating the impact of Hedge Horizon upon Hedging Effectiveness: Evidence from the national stock exchange of India / Mandeep Kaur and Kapil Gupta.

This study investigated the impact of hedge horizon upon hedging effectiveness in Indian equity futures market by comparing hedging performance of near, next and far month futures contracts of the NIFTY50 index and its 17 composite stocks. Hedging effectiveness was measured using two approaches, namely, Variance Reduction approach and RiskReturn approach. The study found that near month futures contracts are most effective when hedge effectiveness is measured using the variance reduction approach, whereas, far month futures contracts are found to be most effective using the risk-return approach. These results imply that for highly risk-averse investors (concerned with only minimization of risk), near month futures contracts enable effective hedging, whereas for less risk-averse investors (concerned with risk as well as return), far month futures contracts offer superior hedge effectiveness. The study also found that coefficient of correlation between spot and futures returns is a significant factor affecting variance reduction of returns and bears a direct relationship with it

The effectiveness of index futures hedging in emerging markets during the crisis period of 2008-2010: Evidence from South Africa

This paper provides an assessment of the comparative effectiveness of four econometric methods in estimating the optimal hedge ratio in an emerging equity market, particularly the South African equity and futures markets. The paper bases the effectiveness of hedging on volatility reduction and minimisation of the coefficient of variation of hedged returns as well as risk-aversion based utility maximisation. The empirical analysis shows that the single equation method estimated by ordinary least squares is the most effective over daily hedging periods. However, the vector error-correction method and multivariate GARCH methods are most effective over weekly and monthly hedging periods