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The purpose of this paper is to determine and contrast the risk mitigating effectiveness from optimal multiproduct time-varying hedge ratios, applied to the margin of a cattle feedlot operation, over single commodity time-varying and naive hedge ratios.

A parsimonious regime-switching dynamic correlations (RSDC) model is estimated in two-stages, where the dynamic correlations among prices of numerous commodities vary proportionally between two different regimes/levels. This property simplifies estimation methods for a large number of parameters involved.

There is significant evidence that resulting simultaneous correlations among the prices (spot and futures) for each commodity attain different levels along the time-series. Second, for in and out-of-sample data there is a substantial reduction in the operation's margin variance provided from both multiproduct and single time-varying optimal hedge ratios over naive hedge ratios. Lastly, risk mitigation is attained at a lower cost given that average optimal multiproduct and single time-varying hedge ratios obtained for corn, feeder cattle and live cattle are significantly below the naive full hedge ratio.

The application studied is limited in that once a hedge position has been set at a particular period, it is not possible to modify or update at a subsequent period.

Agricultural producers, specifically cattle feeders, may profit from a tool using improved techniques to determine hedge ratios by considering a larger amount of up-to-date information. Moreover, these agents may apply hedge ratios significantly lower than one and thus mitigate risk at lower costs.

Feedlot operators will benefit from the potential implementation of this parsimonious RSDC model for their hedging operations, as it provides average optimal hedge ratios significantly lower than one and sizeable advantages in margin risk mitigation.

The purpose of this paper is to examine the potential gains in hedge ratio calculation for agricultural commodities by incorporating market linkages and prices of related commodities into the hedge ratio estimation process.

A vector autoregressive multivariate generalized autoregressive conditional heteroskedasticity (VAR‐MGARCH) model is used to construct a time‐varying correlation matrix for commodity prices across linked markets and across linked commodities. The MGARCH model is estimated using a two‐step approach, which allows for a large system of related prices to be estimated.

In‐sample and out‐of‐sample portfolio variance comparison among no hedge, bivariate GARCH, and MGARCH models indicates that hedge ratios estimated using the MGARCH approach reduce agricultural producers' and commercial consumers' risks in futures market participation.

The application is limited to an examination of Montana wheat markets.

Agricultural producers who use futures markets to reduce market risk will have a better method for determining hedging positions, because MGARCH estimated hedge ratios incorporate more information than hedge ratios estimated using existing practices.

Portfolio variance reduction is analogous to utility improvement for agricultural producers. More efficient hedging strategies can lead to better implementation of futures markets and increased social welfare.

This research substantially extends current literature on agricultural hedge strategies by illustrating the advantages of using an hedge ratio estimation approach that incorporates important information about prices at linked markets and prices of other commodities. Providing evidence that market portfolio variance can be lowered using the multivariate estimation approach, the research offers commercial agricultural producers and consumers a practical tool for improving futures market strategies.

The purpose of this paper is to measure the effectiveness of the hedging with futures currency contracts. Measuring the effectiveness of hedging has become mandatory for Indian companies as the new Indian accounting standards, Ind-AS, specify that the effectiveness of hedges taken by the companies should be evaluated using quantitative methods but leaves it to the company to choose a method of evaluation.

The paper compares three models for evaluating the effectiveness of hedge – ordinary least square (OLS), vector error correction model (VECM) and dynamic conditional correlation multivariate GARCH (DCC-MGARCH) model. The OLS and VECM are the static models, whereas DCC-MGARCH is a dynamic model.

The overall results of the study show that dynamic model (DCC-MGARCH) is a better model for calculating the hedge effectiveness as it outperforms OLS and VECM models.

The new Indian accounting standards (Ind-AS) mandates the calculation of hedge effectiveness. The results of this study are useful for the treasurers in identifying appropriate method for evaluation of hedge effectiveness. Similarly, policymakers and auditors are benefitted as the study provides clarity on different methods of evaluation of hedging effectiveness.

Many previous studies have evaluated the efficiency of the Indian currency futures market, but with rising importance of hedging in the Indian companies, Reserve Bank of India’s initiatives and encouragement for the use of futures for hedging the currency risk and now the mandatory accounting requirement for measuring hedging effectiveness, it has become more relevant to evaluate the effectiveness of hedge. To the authors’ best knowledge, this is one of the first few papers which evaluate the effectiveness of the currency future hedging.

This paper aims to attempt to re-capture the stock market contagion effect from the US to the BRIC equity markets during the recent global financial crisis in a multivariate framework. Apart from this, the study also identifies optimal portfolio hedging strategies to minimize the underlying portfolio risk during the period undertaken for the purpose of study.

To account for the dynamic interactions, the study uses vector autoregression (p) dynamic conditional correlation (DCC)-asymmetric generalized autoregressive conditional heteroskedastic (1,1) model in a multivariate framework, coupled with a monthly heat map relating to the co-movement between the US and the BRIC equity markets during the period 2007-2009. Finally, by following the studies, Hammoudeh et al. (2010) and Syriopoulos et al. (2015), the time-varying optimal portfolio hedge ratios and weights are computed.

The results report a contagion impact of the US subprime crisis (following the collapse of the Lehman Brothers) on the Indian and Russian stock markets only. On the other hand, a higher degree of interdependence between the US and Brazilian market has been observed. The US and Chinese equity markets indicate a relatively lower level of interdependence among themselves. The optimal hedge ratios are found to be most effective for a portfolio comprising the US and Chinese stocks even during the crisis period. A US investor should invest approximately 30 cents in the Indian market and rest of the 70 cents in the US market in a US$1 portfolio to minimize the portfolio risk without lowering the expected returns. During the crisis period (2007-2009), the optimal portfolio weights indicate a higher weightage to the BRIC stocks.

The results support the construction of optimal US–BRIC stock portfolios and provide an insight to the investors and policy makers both domestic as well as international, with regard to the contagion impact and interdependence, especially during a crisis period.

The study uses a DCC model in a multivariate framework instead of bivariate, wherein all the markets are factored into a single interaction framework across a very long period (2004-2014). Second, a heat map of monthly correlation combinations has been created for the period 2007-2009, to comprehend the contagion impact or interdependence among the markets. Finally, the study ascertains time-varying optimal hedge ratios and portfolio weights for a two asset portfolio, from a US investor viewpoint, making the study first of its kind in all the perspectives.

The purpose of this paper is to document stylized features and market behaviour of the Canadian Bankers' Acceptance Futures (BAX) contract; and outlook for the BAX contract as the dominant instrument to manage Canadian short‐term interest rate exposure.

The paper adopts GARCH methodology to model the time‐varying nature of the volatility of prices in the context of hedging and presents a time‐varying estimation of the hedge ratios between the BAX contract and major Canadian money market instruments.

The key finding is that the growth of the BAX Market hinges on the further development of the Canadian money market and its appeal to the international investor.

The paper demonstrates the suitability of the BAX contract as a tool in managing Canadian short‐term interest rate exposure for both domestic and international investors.

This paper aims to investigate the efficiency of different hedging strategies for an investor holding a portfolio of foreign currency bonds.

The simplest strategies of no hedge and fully hedged are compared with the more sophisticated strategies of the ordinary least squares (OLS) approach and the optimal hedge ratios found by the dynamic conditional correlation-generalised autoregressive conditional heteroskedasticity approach.

The sophisticated hedging strategies are found to be superior to the simple strategies because they lower the portfolio risk in domestic currency terms and improve the Sharpe ratios for multi-asset portfolios. The analyses also show that both the OLS and dynamic hedging strategies imply holding a limited carry position by being long in high-yielding currencies but short in low-yielding currencies.

The performance of multi-currency portfolios is examined using more realistic assumptions than in the previous literature, including a weekly frequency and a constraint of no short selling. Furthermore, carry trades are shown to be part of an optimal portfolio.

This paper provides a critique of minimum variance hedging using futures. The paper develops the conventional minimum variance hedge ratio (MVHR) and discusses its estimation. A review of the wide variety of alternative methods used to construct MVHRs is then performed. These methods highlight many of the potential limitations in the conventional framework. The paper argues that the literature should focus more on the assumptions underlying the conventional MVHR, rather than improving the techniques used to estimate the conventional MVHR.

This study explores hedging strategies that use the KTB futures to hedge the price risk of the KTB spot portfolio. The study establishes the price sensitivity, risk-minimization, bivariate GARCH (1,1) models as hedging models, and analyzes their hedging performances. The sample period covers from September 29, 1999 to September 18, 2001. Time-matched prices at 11:00 (11:30) of the KTB futures and spot were used in the analysis. The most important findings may be summarized as follows. First, while the average hedge ration of the price sensitivity model is close to one, both the risk-minimization and GARCH model exhibit hedge ratios that are substantially lower than one. Hedge ratios tend to be greater for daily data than for weekly data. Second, for the daily in-sample data, hedging effectiveness is the highest for the GARCH model with time-varying hedge ratios, but the risk-minimization model with constant hedge ratios is not far behind the GARCH model in its hedging performance. In the case of out-of-sample hedging effectiveness, the GARCH model is the best for the KTB spot portfolio, and the risk-minimization model is the best for the corporate bond portfolio. Third, for daily data, the in-sample hedge shows a better performance than the out-of-sample hedge, except for the risk-minimization hedge against the corporate bond portfolio. Fourth, for the weekly in-sample hedges, the price sensitivity model is the worst and the risk-minimization model is the best in hedging the KTB spot portfolio. While the GARCH model is the best against the KTB +corporate bond portfolio, the risk-minimization model is generally as good as the GARCH model. The risk-minimization model performs the best for the weekly out-of-sample data, and the out-of-sample hedges are better than the in-sample hedges. Fifth, while the hedging performance of the risk-minimization model with daily moving window seems somewhat superior to the traditional risk-minimization model when the trading volume increased one year after the inception of the KTB futures, on the average the traditional model is better than the moving-window model. For weekly data, the traditional model exhibits a better performance. Overall, in the Korean bond markets, investors are encouraged to use the simple risk-minimization model to hedge the price risk of the KTB spot and corporate bond portfolios.

In this paper, the authors aim to investigate the return, volatility and correlation spillover effects between the crude oil market and the various Indian industrial sectors (automobile, financial, service, energy, metal and mining, and commodities sectors) in order to investigate optimal portfolio construction and to estimate risk minimizing hedge ratios.

The authors compare bivariate generalized autoregressive conditional heteroskedasticity models (diagonal, constant conditional correlation and dynamic conditional correlation) with the vector autoregressive model as a conditional mean equation and the vector autoregressive moving average generalized autoregressive conditional heteroskedasticity model as a conditional variance equation with the error terms following the Student's t distribution so as to identify the model that would be appropriate for optimal portfolio construction and to estimate risk minimizing hedge ratios.

The authors’ results indicate that the dynamic conditional correlation bivariate generalized autoregressive conditional heteroskedasticity model is better able to capture time‐dynamics in comparison to other models, based on which the authors find evidence of return and volatility spillover effects from the crude oil market to the Indian industrial sectors. In addition, the authors find that the conditional correlations between the crude oil market and the Indian industrial sectors change dynamically over time and that they reach their highest values during the period of the global financial crisis (2008‐2009). The authors also estimate risk minimizing hedge ratios and oil‐stock optimal portfolio holdings.

This paper has empirical originality in investigating the return, volatility and correlation spillover effects from the crude oil market to the various Indian industrial sectors using BVGARCH models with the error terms assumed to follow the Student's t distribution.

The hedging effectiveness of real estate investment trust (REIT) futures as a critical issue in response to the global REIT market has been extremely volatile in recent years, however few studies have been placed on this area. This study aims to fill in this gap and examine the hedging effectiveness of Australian and Japanese REIT futures over 2002‐2010.

The analysis of this study involves two stages. The first stage is to estimate optimal hedge ratios. A variety of hedging methods is employed, including a traditional hedge, an ordinary least squares (OLS) model and a bivariate GARCH model. Thereafter, the hedging effectiveness of these strategies is assessed individually.

The empirical results show REIT futures are effective hedging instruments in which a risk reduction of 37 per cent‐78 per cent (34 per cent‐52 per cent) for Australian (Japanese) REITs is evident. Importantly, the results also reveal that REIT futures outperform other hedging instruments in which a weaker risk reduction is found by stock, interest rate and foreign currency futures contracts. Moreover, the hedging effectiveness of REIT futures is dynamic and varies over time.

The findings enable more informed and practical investment decision‐making regarding the role of REIT futures in risk management.

This paper, as far as the authors are aware, is the first study to offer empirical evidence of the risk‐reduction effectiveness of REIT futures. The hedging effectiveness of REIT futures is also compared to other hedging instruments for the first time.