Cross Hedging Research Articles

Crude oil futures to manage the price risk of textile equities: An empirical evidence from India

The textile sector in India is the oldest manufacturing sector. As the raw materials for this sector are sourced from the petrochemical industries, the earnings of Indian textile companies are dependent on the crude oil price. The crude price in the international market has become more volatile and hence, the equity price of Indian textile companies has become more volatile. This study aims to develop two price risk management strategies for Indian textile equities. Using the vector autoregressive (VAR) model, a price forecast model, further the possibility of cross hedge for textile equities with the help of crude futures is examined using the Granger causality test and Pearson correlation statistics. The results of the study showed that crude futures price in India is one of the price determinants of textile industry stock prices.

CAN CRUDE OIL FUTURES BE THE GOOD HEDGING TOOL FOR TYRE EQUITIES? EVIDENCE FROM INDIA

This article examines the cross-hedging performance of crude futures against the tyre equity futures to hedge the tyre equity stocks. Three multivariate conditional volatility models, namely constant conditional correlation (CCC), dynamic conditional correlation (DCC) and diagonal BEKK are applied. Using the conditional covariance and variance from the MGARCH estimates, the optimal hedge ratios (OHRs) are computed. The results of this study show that the volatility spillover exists between the returns of crude oil futures and tyre equity. However, for tyre equities, the best cross hedge is tyre equity futures rather than crude futures. All the MGARCH estimates show better hedging possibility with tyre equity futures, particularly MRF futures.Keywords: CCC; Crude future; DCC; Diagonal BEKK; Tyre equity; Tyre equity futuresJEL Classifications: G21; G30DOI: https://doi.org/10.32479/ijeep.11863

Crude oil futures to manage the price risk of natural rubber: Empirical evidence from India

The trading of natural rubber derivatives in the Indian commodity exchanges was banned several times in the past. Hence, in India, the derivatives on natural rubber are not traded actively and regularly. We have examined the possibility of a forecast model and a cross hedge tool for the natural rubber price by using crude oil futures in India. Results of the Johansen cointegration test proved that there is no cointegration equation in the model; hence, there is no scope to develop long-run models or error correction models. We have developed a vector autoregressive [VAR(2)] model to forecast the rubber price, and we examined the possibility of a cross hedge for natural rubber further by using the Pearson correlation coefficient and Granger causality test. We have extended our research to a structural VAR analysis to examine the effect of crude futures and exchange rate shocks on the natural rubber price. Our results showed that there is a short-term relationship between the crude oil futures price, the exchange rates of the US dollar to the Indian rupee, the Malaysian ringgit to the Indian rupee and the Thai baht to the Indian rupee; and the natural rubber price in India. The effort of policymakers to cause the Indian rupee to appreciate against the Thai baht and Malaysian ringgit may increase the natural rubber price in India. Natural rubber traders, growers and consumers can use crude futures to hedge the price risk. The Indian Rubber Board can suggest the VAR(2) model to predict the short-run price for natural rubber.

Cross hedging with stock index futures

This paper examines the cross hedging effectiveness between UK FTSE100 and world stock index futures from developed and emerging markets: the US, Australia, Brazil, Japan, Hong Kong, Korea and Malaysia. Our daily dataset spans from August 2002 through November 2019. We apply the OLS, VECM and Maximal Overlap Discrete Wavelet Transform (MODWT) to calculate the optimal cross hedge ratio and cross hedging effectiveness. Our empirical results show that the US E-Mini DJIA$5 futures contract is the best cross hedging instrument for the UK FTSE100, followed by the Australia S&P/ASX 200. The multiscale cross hedging effectiveness results from the MODWT estimation suggest the optimal hedging period of more than 256 days with the US E-Mini DJIA$5 and Australia S&P/ASX 200 futures.

Relationships among US S&P500 Stock Index, its Futures and NASDAQ Index Futures with Volatility Spillover and Jump Diffusion: Modeling and Hedging Performance

This study takes the US S&P500 stock index cash, futures and NASDAQ stock index futures as the main research objects, and applies the ARJI (autoregressive jump intensity model) VEC GJR-GARCH model to examine the co-integration, volatility spillover, jump behavior and hedge performance of the three markets. With the rapid circulation of new information, the financial market will often fluctuate under the impact of new information. Investors will have different and timely responses to emergencies, and this event will have an impact on the stock market. When the event is unexpected or abnormal, the financial market will have huge fluctuations, and this kind of fluctuation is a jump. The empirical results found that the three markets have linkages and volatility spillover effects, and there are indeed discontinuous jumps. Two-way volatility spillovers between S&P500 index cash and futures, and only one-way volatility spillovers from S&P500 futures to the Nasdaq futures market. International investors need to consider information from their own-market volatility (risk) as well as information on volatility spillovers (risk) from other markets. The jump frequency is not a fixed constant, that is, the jump frequency (strength) generated by abnormal information changes over time. In addition, the results of this research also found that the ARJI VEC GJR-GARCH model can better capture the risk of fluctuations in price discontinuities after adding jump factors to the hedging performance estimated by the ARJI VEC GJR-GARCH model. The hedging performance can be more effective, which is conducive to investors' risk management decisions. Also, the performance of direct hedging that is better than the performance of cross hedging.

Dynamic Cross Hedging Effectiveness between Gold and Stock Market Based on Downside Risk Measures: Evidence from Iran Emerging Capital Market

Dynamic Cross Hedging Effectiveness between Gold and Stock Market Based on Downside Risk Measures: Evidence from Iran Emerging Capital Market

Crude Oil Futures to Manage the Price Risk of Natural Rubber: Empirical Evidence from India

The trading of natural rubber derivatives in the Indian commodity exchanges was banned several times in the past. Hence, in India, the derivatives on natural rubber are not traded actively and regularly. We have examined the possibility of a forecast model and across hedge tool for the natural rubber price by using crude oil futures in India. Results of the Johansen cointegration test proved that there is no cointegration equation in the model; hence, there is no scope to develop long-run models or error, correction models. We have developed a vector autoregressive [VAR(2)] model to forecast the rubber price, and we examined the possibility of a cross hedge for natural rubber further by using the Pearson correlation coefficient and Granger causality test. We have extended our research to a structural VAR analysis to examine the effect of crude futures and exchange rate shocks on the natural rubber price. Our results showed that there is a short-term relationship between the crude oil futures price, the exchange rates of the US dollar to the Indian rupee, the Malaysian ringgit to the Indian rupee, and the Thai baht to the Indian rupee; and the natural rubber price in India. The effort of policymakers to cause the Indian rupee to appreciate against the Thai baht and Malaysian ringgit may increase the natural rubber price in India. Natural rubber traders, growers, and consumers can use crude futures to hedge the price risk. The Indian Rubber Board can suggest the VAR(2) model predict the short-run price for natural rubber.

SOME NOTES ABOUT THE MARTINGALE REPRESENTATION THEOREM AND THEIR APPLICATIONS

An important theorem in stochastic finance field is the martingale representation theorem. It is useful in the stage of making hedging strategies (such as cross hedging and replicating hedge) in the presence of different assets with different stochastic dynamics models. In the current paper, some new theoretical results about this theorem including derivation of serial correlation function of a martingale process and its conditional expectations approximation are proposed. Applications in optimal hedge ratio and financial derivative pricing are presented and sensitivity analyses are studied. Throughout theoretical results, simulation-based results are also proposed. Two real data sets are analyzed and concluding remarks are given. Finally, a conclusion section is given.

Dual and single hedging strategy: a novel comparison from the direct and cross hedging perspective

PurposeThe purpose of this paper is to deeply study and compare the dual and single hedging strategy, from the direct and cross hedging perspective.Design/methodology/approachThe authors not only first consider the dual hedge of integrated risks in this oil prices and foreign exchange rates setting but also make a novel comparison between the dual and single hedging strategy from a direct and cross hedging perspective. In total, six econometric models (to conduct one-step-ahead out-of-sample rolling estimation of the optimal hedge ratio) and two hedging performance criteria are employed in two different hedging backgrounds (direct and cross hedging).FindingsResults show that in the direct hedging background, a dual hedge cannot outperform the single hedge. But in the cross dual hedging setting, a dual hedge performs much better, possibly because the dual hedge brings different levels of advantages and disadvantages in the two different settings and the superiority of the dual hedge is more obvious in the cross dual hedging setting.Originality/valueThe existing literature that deals with oil prices and foreign exchange rates mostly concentrates on their relationship and comovements, while the dual hedge of integrated risks in this setting remains underresearched. Besides, the existing literature that deals with dual hedge gets its conclusions only based on a single specific background (direct or cross hedging) and lacks deeper investigation. In this paper, the authors expand the width and depth of the existing literature. Results and implications are revealing.

Cross Hedging Effectiveness of Real Estate Securities Exchange Traded Funds

We investigate hedging effectiveness of four REIT Exchange Traded Funds in hedging seven real estate securities returns for the United States, Europe, and Asia through R-Squared, hedge ratio, variance reduction (VR) and utility maximization metrics. The analyses cover different full sample and sub-sample periods from 2000 to 2010 (inclusive) to document the performances of the hedge during periods of high and low volatility. The results show that the ETFs were very effective in hedging EREIT and all the sampled real estate securities in Europe and Asia. Second, VECM hedge marginally outperformed OLS hedge. Third, we find that hedging effectiveness evidenced by VR does not necessarily equate to economic viability. Therefore VR must be used together with UIs to determine viability of hedging effectiveness. Finally, given different levels of risk aversion vis-à-vis expected utility, it is advisable/inadvisable to hedge during high/low volatility periods.

The nexus of trade-weighted dollar rates and the oil prices: an asymmetric approach

PurposeThis paper investigates the dynamic relationship between the trade-weighted dollar exchange rates and the oil prices in the world market. Monthly data during 1980–2017 are used for this purpose.Design/methodology/approachThe symmetric and asymmetric generalized impulse response functions are estimated for these important economic indicators.FindingsThe empirical findings show that if the dollar rate increases (i.e. the dollar depreciates), the oil price will increase. The reverse relationship is also supported empirically meaning that an increase in the oil price will results in a significant depreciation of the dollar rate. Based on the asymmetric impulses responses, it can also be claimed that the negative interaction is only significant for the positive changes and not for the negative ones. Thus, the underlying variables are negatively interrelated only for the positive shocks since a negative shock from any variable does not seem to have any significant impact on the other variable. These results have implications for cross hedging of price risk.Originality/valueTo the best knowledge, this is the first attempt to investigate the relationship between the dollar weighted exchange rate and the oil pieces via the asymmetric impulse response functions. Both of these variables and their interactions are very important for investors as well as policy makers worldwide.

Composite hedge and utility maximization for optimal futures hedging

To investigate the advantages of the composite hedge over the single hedge, this paper uses the ordinary least squares (OLS), dynamic conditional correlation (DCC), asymmetric dynamic conditional correlation (ADCC), copula-DCC, copula-ADCC, generalized orthogonal generalized autoregressive conditional heteroskedastic (GO-GARCH) and generalized orthogonal Glosten-Jagannathan-Runkle (GO-GJR) models to estimate the hedge ratio in the minimum variance and expected utility maximization objective under single and composite cross hedge settings. Under all the hedging performance criteria, the composite hedge is better than the single hedge in most circumstances. In addition, the copula-ADCC, GO-GARCH and GO-GJR models perform better than other relatively simple models. In this cross composite hedging context, the naïve strategy can be beaten. The findings are robust to model specifications and contexts.

The Feasibility of Cross Hedging Wood Pulp with CME Lumber Futures

The main objective of the study is to determine whether the CME (Chicago Mercantile Exchange) random length lumber futures can be used as a cross hedging vehicle for the wood pulp (LBKP and NBKP). In order for the cross hedging to be feasible, there should be a strong positive relationship between the cash price and the futures price. This study conducted rigorous statistical analyses such as cointegration test and Granger causality test to examine the price relationship between CME lumber futures and wood pulp. The empirical analyses suggest that CME random length lumber futures can not be used as a potential cross hedging vehicle for wood pulp.

Organic Wheat Prices and Premium Uncertainty: Can Cross Hedging and Forecasting Play a Role?

We compare the volatility of organic wheat prices to that of conventional wheat prices using historical measures. To reduce uncertainty, we examine the possibility of cross hedging using conventional wheat futures and the ability of futures to forecast the organic premium. Results provide evidence that conventional futures can be used to cross hedge organic wheat price risk,but results depend on the method used to impute the missing values. We also find a long-run equilibrium relationship between organic wheat prices and conventional wheat futures prices.Finally, futures prices contain some information useful in predicting organic prices in the short run.

Effective cross hedging: Evidence from physical crude palm oil and its non-interrelated energy futures contracts

Recent researchers found that Crude Palm Oil Futures contract (FCPO) in Bursa Malaysia Derivatives is no longer an effective hedging tool to mitigate the price risk in cash market due to the excessive speculation trading activities. This is very alarming to the hedgers hence possible hedge pair alternatives to crude palm oil physical must be identified to ensure that the hedging can be executed effectively. Therefore in this study, Ordinary Least Square, bivariate VAR and bivariate VECM were used to examine whether the non-interrelated energy futures contracts could serve as effective cross-hedging mechanisms for the CPO. Weekly data of agricultural and energy futures contracts from Intercontinental Exchange (ICE), New York Mercantile Exchange (NYMEX), and Tokyo Commodity Exchange (TOCOM) are employed to cross hedge the physical crude palm oil prices. The study starts from 2006 until 2016. Empirical results indicate that bivariate VECM gives more hedging variance reduction. Surprisingly, overall FCPO is still the best futures contract for hedging purposes while Japanese crude oil futures (TOCOM) represents the energy futures market as the best cross hedge alternatives for CPO.

Cross Hedging Using Prediction Error Weather Derivatives for Loss of Solar Output Prediction Errors in Electricity Market

Predicting future solar conditions is important for electricity industries with solar power generators to quote a day-ahead sales contract in the electricity market. If a prediction error exists, the market-monitoring agent has to prepare another power generation resource to immediately compensate for the shortage, resulting in an additional cost. In this context, a penalty may be required depending on the size of the prediction error, which may lead to a significant loss for solar power producers. Because the main source of such losses is from prediction errors of solar conditions, they can instead effectively utilize a derivative contract based on solar prediction errors. The objective of this work is to provide such a derivative contract, namely, a prediction error weather derivative. First, defining a certain loss function, we measure the hedge effect of the derivative on solar radiation prediction error, thereby verifying that the existing hedging method for wind power can also be applied to solar power generation with periodic trends. By introducing the temperature derivative on the absolute prediction error, we also propose a cross-hedging method, where we demonstrate not only a further variance reduction effect when used with solar radiation derivatives, but also a certain hedge effect obtained even when only the temperature derivative is used. For temperature derivative pricing and optimal contract volume estimation, we propose a method using a tensor-product spline function that simultaneously incorporates the smoothing conditions of both the direction of intraday time trend and seasonal trend, and consequently verify its effectiveness.

EFFECTIVE CROSS HEDGING: EVIDENCE FROM PHYSICAL CRUDE PALM OIL AND ITS INTER-RELATED AGRICULTURAL FUTURES CONTRACTS

Since its establishment, Crude Palm Oil futures contract (FCPO) has been used to directly hedge its physical crude palm oil (CPO). However, due to the excessive speculation activities on crude palm oil futures market, it has been said to be no longer an effective hedging tool to mitigate the price risk of its underlying physical market. This triggers the need for market players to find possible alternatives to ensure that the hedging role can be executed effectively. Thus this investigation attempts to examine whether other inter-related grains and oil seed futures contracts could serve as effective cross-hedging mechanisms for the CPO. Weekly data of inter-related futures contracts from Chicago Board of Trade (CBOT) and Dalian Commodity Exchange (DCE) are employed to cross hedge the physical crude palm oil prices. The study starts from 2006 until 2016. Empirical results indicate that FCPO is still the best futures contract for hedging purposes while Chicago Soybean (CBOTBO) provides second best alternative if cross-hedging is considered.
 Keywords: Crude palm oil, Crude palm oil futures, Cross Hedging, Optimal Hedge Ratio, Effective Hedging

Cross Hedging Stock Sector Risk with Index Futures by Considering the Global Equity Systematic Risk

This article investigates the effectiveness of TAIEX (Taiwan Stock Exchange) futures, Taiwan 50 futures, and nonfinance nonelectronics subindex (NFNE) futures for cross hedging the price risk of stock sector indices traded on the Taiwan stock exchange. A state-dependent volatility spillover GARCH hedging strategy is developed to capture the regime switching global equity volatility spillover effect. Empirical results show that the NFNE futures exhibit superior effectiveness as an instrument for hedging stock sector exposures compared with the TAIEX and Taiwan 50 futures. Simultaneous hedge using both NFNE and MSCI (Morgan Stanley Capital International) world index futures further improves the hedging effectiveness compared with the hedging strategy using only the NFNE futures. This shows the importance of hedging the global equity systematic risk of stock sectors by considering the comovement between domestic and global equity markets.

Correlation asymmetry and implication on hedging

The paper studies the correlation asymmetry between currency spot and futures returns and its implication on hedging effectiveness using alternative multivariate GARCH models and different hedging strategies. For this purpose, daily data of EUR spot and futures returns are used to present a direct hedging strategy. A cross hedging strategy is also proposed using TND spot and EUR futures returns. Dynamic hedging is implemented using five multivariate GARCH models. The diagonal VECH and BEKK models are chosen among the covariance models. The CC-GARCH, DCC and GDCC represent the correlation models. The empirical results show that correlation between EUR spot and futures returns as well as between TND spot and EUR futures returns exhibit asymmetric behaviour. Moreover, the asymmetric diagonal VECH gives the best performance in terms of portfolio risk reduction in both strategies showing that covariance models are better than correlation models in modelling correlation asymmetry.

Correlation asymmetry and implication on hedging

The paper studies the correlation asymmetry between currency spot and futures returns and its implication on hedging effectiveness using alternative multivariate GARCH models and different hedging strategies. For this purpose, daily data of EUR spot and futures returns are used to present a direct hedging strategy. A cross hedging strategy is also proposed using TND spot and EUR futures returns. Dynamic hedging is implemented using five multivariate GARCH models. The diagonal VECH and BEKK models are chosen among the covariance models. The CC-GARCH, DCC and GDCC represent the correlation models. The empirical results show that correlation between EUR spot and futures returns as well as between TND spot and EUR futures returns exhibit asymmetric behaviour. Moreover, the asymmetric diagonal VECH gives the best performance in terms of portfolio risk reduction in both strategies showing that covariance models are better than correlation models in modelling correlation asymmetry.