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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.

This paper assesses the co-movement between Pax gold and six fiat currencies. It also investigates the optimal time-varying hedge ratios in order to examine the properties of Pax gold as a diversifier and hedge asset.

This paper examines the volatility spillover between Pax gold and fiat currencies using the framework of wavelet analysis, BEKK-GARCH models and Range DCC-GARCH. Moreover, this paper proposes to use the covariance and variance structure obtained from the new range DCC-GARCH framework to estimate the time-varying optimal hedge ratios, the optimal weighs and the hedging effectiveness.

Wavelet coherence method reveals that, at low frequency, large zone of co-movements appears for the pairs Pax gold/EUR, Pax gold/JPY and Pax gold/RUB. Further, the BEKK results show unidirectional (bidirectional) transmission effects between Pax gold and EUR, GBP, JPY and CNY (INR, RUB) fiat currencies. Moreover, the Range DCC results show that the Pax gold and the fiat currency returns are weakly correlated with low coefficients close to zero. Thus, Pax gold seems to serve as a safe haven asset against the systematic risk of fiat currency markets. In addition, the results of optimal weights show that rational investor should invest more in Pax gold and less in fiat currencies. Concerning the hedge ratios results, the findings reveal that the INR (JPY) fiat currency appears to be the most expensive (cheapest) hedge for the Pax-gold market. However, the JPY’s fiat currency appears to be the cheapest one. As for hedging effectiveness results, the authors found that hedging strategies including fiat currencies–Pax gold pairs are most likely to sharply decrease the portfolio’s risk.

A comprehensive understanding of the relationship between Pax Gold and fiat currencies is crucial for refining portfolio strategies involving cryptocurrencies. This research underscores the significance of grasping volatility transmissions between these currencies, providing valuable insights to guide investors in their decision-making processes. Moreover, it encourages further exploration into the interdependencies of digital currencies. Additionally, this study sheds light on effective contagion risk management, particularly during crises such as Covid-19 and the Russia–Ukraine conflict. It underscores the role of Pax Gold as a safe-haven asset and offers practical guidance for adjusting portfolios across various economic conditions. Ultimately, this research advances our comprehension of Pax Gold’s risk-return profile, positioning it as a potential hedge during periods of uncertainty, thereby contributing to the evolving literature on cryptocurrencies.

This study’s primary value lies in its pioneering empirical examination of the time-varying correlations and scale dependence between Pax Gold and fiat currencies. It goes beyond by determining optimal time-varying hedge ratios through the innovative Range-DCC-GARCH model, originally introduced by Molnár (2016) and distinguished by its incorporation of both low and high prices. Significantly, this analysis unfolds within the unique context of the Covid-19 pandemic and the Russian–Ukrainian conflict, marking a novel contribution to the field.

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.

This study examines the dynamics of the comovement and causal relationship between conventional (Bitcoin, Ethereum and Binance coin) and Islamic (OneGram, X8X token and HelloGold) cryptocurrencies.

This study uses wavelet coherence approach to examine the time-varying lead-lag relationship between conventional and Islamic cryptocurrencies. Furthermore, the authors use BEKK-GARCH model to estimate the optimal weights, hedge ratio and hedging effectiveness in pre-COVID-19 and during the COVID-19 period.

The authors find no significant comovement in pre-COVID-19. However, the authors find significant positive comovement in conventional and Islamic cryptocurrencies at the beginning of the pandemic, and in most cases, conventional cryptocurrencies are leading. X8X and HelloGold have no/weak correlation with conventional cryptocurrencies, implying that investors can diversify the risk by making an Islamic and conventional cryptocurrencies portfolio. The authors also calculate the optimal weights, hedge ratio and hedging effectiveness using the BEKK-GARCH model. Based on the optimal weights, for the portfolios of conventional–Islamic cryptocurrencies, investors are suggested to increase their investment in Islamic cryptocurrencies during the COVID-19 than normal period. The results of hedge ratios show that hedging costs are higher during COVID-19 than before.

The findings of the paper offer several practical policy implications for investors, portfolio manager, Shariah advisors and policymakers pertaining to asset allocation, risk management, forecasting and diversification. Specifically, investors can maximize the risk adjusted returns of their conventional cryptocurrencies portfolio by adding some portions of Islamic cryptocurrencies. Considering the comovement is time-varying, investors/manager should adjust their investment strategies frequently. For the entrepreneurs in crypto-industry, it is advised to introduce new Islamic cryptocurrencies, as it has a huge growth potential because of their distinct features and performance.

This is the first study that explores the linkages between conventional and Islamic cryptocurrencies, therefore this study extends the literature of Islamic finance, stablecoins and cryptocurrencies in pre-COVID-19 and during COVID-19 period. The study results provide insights to conventional crypto investor on how to manage their portfolio during normal and turbulent period.

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 study aims to investigate the relationship between stock markets, environmental, social and governance (ESG) factors and Shariah-compliant in an integrated framework.

The authors employ the multivariate factor stochastic volatility (mvFSV) framework to extract the volatility of the different sectoral indices. Based on this evidence, the authors employ the quantile vector autoregressive (QVAR) approach to examine the dynamic spillover connectedness among the aforementioned indices.

The study emphasizes the following major findings: (1) significant time-varying spillover connectedness across quantiles, (2) bidirectional and asymmetric spillover effect among the ESG index and the other sectoral indices, (3) the strength of spillover connectedness is time-varying across quantiles, (4) based on the perspective of portfolio optimization, ESG market is a significant strong forecasting contributor to conventional and Shariah-compliant markets, (5) overall, the findings point out serious quantile pass-through effect among ESG index and the other sectoral indices during the COVID-19 health crisis.

This study extends the previous literature in the following ways. First, to the best of the researchers’ knowledge, none of the existing studies have investigated the relationship between stock markets, ESG factors and Shariah-compliant in an integrated framework. Second, this study extends the previous scholarships by applying the mvFSV. Third, the authors propose a new rolling version to estimate dynamic spillovers, namely the rolling-window quantile VAR method. This approach provides a great advantage in computing the dynamics of return and variance spillover between variables in terms not only of the overall factor but also of the net (pairwise) aspect.

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.