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Article
Publication date: 23 September 2022

Rania Zghal, Amel Melki and Ahmed Ghorbel

This present work aims at looking into whether or not introducing commodities in international equity portfolios helps reduce the market risk and if hedging is carried out…

Abstract

Purpose

This present work aims at looking into whether or not introducing commodities in international equity portfolios helps reduce the market risk and if hedging is carried out with the same effectiveness across different regional stock markets.

Design/methodology/approach

The authors determine the optimal hedge ratios and hedging effectiveness of a number of commodity-hedged emerging and developed equity markets, using three versions of MGARCH model: DCC, ADCC and GO-GARCH. The authors also use a rolling window estimation procedure for the purpose of constructing out-of-sample one-step-ahead forecasts of dynamic conditional correlations and optimal hedge ratios.

Findings

Empirical results evince that commodities significantly display effective risk-reducing hedge instruments in short and long runs. The main finding is that commodities do not seem to hedge regional stock markets in the same way. They tend to provide evidence of a rather effective hedging regarding mainly the East European and Latin American stock markets.

Originality/value

The authors study whether commodities can hedge stock markets at regional context and if hedging effectiveness differ from one region to another.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 15 September 2022

Sei Jeong and Munisamy Gopinath

This study aims to investigate the role of international price volatility and inventories on domestic market price dynamics in the case of agricultural commodities.

Abstract

Purpose

This study aims to investigate the role of international price volatility and inventories on domestic market price dynamics in the case of agricultural commodities.

Design/methodology/approach

A structural model is employed to uncover relationships among commodity price, price volatility, inventories and convenience yield. Monthly producer price data along with annual data on trade, consumption, inventories and tariffs for 71 countries and 13 commodities covering 2010–2019 are assembled to estimate the model. With a first-stage Least Absolute Shrinkage and Selection Operator (LASSO) estimator to identify the best instrument set, a nonlinear approach is used to estimate the model.

Findings

Results show that international market information plays a critical role in domestic market price dynamics. International price volatility has a stronger effect on domestic prices than that of international inventories.

Research limitations/implications

Current upheaval in commodity markets requires an understanding of how prices move together and inventories affect that movement. A country's internal price is not independent of the effects of global market events.

Originality/value

Although hypotheses exist that global market information (volatility and inventories) helps countries manage domestic commodity prices, there have been limited studies on this relationship, especially with a structured model and cross-country data.

Details

Journal of Agribusiness in Developing and Emerging Economies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-0839

Keywords

Article
Publication date: 12 May 2021

Mazin A.M. Al Janabi

This paper aims to examine from commodity portfolio managers’ perspective the performance of liquidity adjusted risk modeling in assessing the market risk parameters of a…

Abstract

Purpose

This paper aims to examine from commodity portfolio managers’ perspective the performance of liquidity adjusted risk modeling in assessing the market risk parameters of a large commodity portfolio and in obtaining efficient and coherent portfolios under different market circumstances.

Design/methodology/approach

The implemented market risk modeling algorithm and investment portfolio analytics using reinforcement machine learning techniques can simultaneously handle risk-return characteristics of commodity investments under regular and crisis market settings besides considering the particular effects of the time-varying liquidity constraints of the multiple-asset commodity portfolios.

Findings

In particular, the paper implements a robust machine learning method to commodity optimal portfolio selection and within a liquidity-adjusted value-at-risk (LVaR) framework. In addition, the paper explains how the adapted LVaR modeling algorithms can be used by a commodity trading unit in a dynamic asset allocation framework for estimating risk exposure, assessing risk reduction alternates and creating efficient and coherent market portfolios.

Originality/value

The optimization parameters subject to meaningful operational and financial constraints, investment portfolio analytics and empirical results can have important practical uses and applications for commodity portfolio managers particularly in the wake of the 2007–2009 global financial crisis. In addition, the recommended reinforcement machine learning optimization algorithms can aid in solving some real-world dilemmas under stressed and adverse market conditions (e.g. illiquidity, switching in correlations factors signs, nonlinear and non-normal distribution of assets’ returns) and can have key applications in machine learning, expert systems, smart financial functions, internet of things (IoT) and financial technology (FinTech) in big data ecosystems.

Article
Publication date: 11 October 2021

Manogna R.L. and Aswini Kumar Mishra

Market efficiency leads to transparent and fair price discovery of commodity markets, thus enhancing the value chain for competitive benefit. The purpose of this paper is…

Abstract

Purpose

Market efficiency leads to transparent and fair price discovery of commodity markets, thus enhancing the value chain for competitive benefit. The purpose of this paper is to investigate the market efficiency of Indian agricultural commodities at spot, futures and mandi markets apart from exploring price risk management in these markets.

Design/methodology/approach

This study uses Johansen co-integration, vector error correction model and granger causality for analyzing market efficiency of the nine most liquid agricultural commodities across three markets, namely, spot, futures and mandi. All these nine commodities are traded on National Commodity and Derivatives Exchange.

Findings

The statistical results indicate price discovery exists in the mandi market and spot market leading to futures prices. Mandi price returns are seen to negatively influence futures returns in the case of cotton seed, guar seed and spot returns in the case of jeera, coriander and chana. For castor seed, the three markets are seen to have no long run relationship. The results of Granger causality reveal short run relationship between all the three markets in the case of soybean seed and coriander. In these commodities, prices in all three markets are capable of predicting the prices in the other markets. For the case of cottonseed, Rape Mustard seed, jeera, guar seed, the results indicate unidirectional causality between the mandi markets and the other two markets.

Research limitations/implications

These results shall facilitate policymakers to explore intervention through integrated agri-platform (IAP) in price discovery and market efficiency.

Practical implications

The results of this study are useful in understanding the price discovery of mandi markets and its role in the spot and futures market. Agricultural commodities price discovery depends upon the integration of all these three markets. Introduction of IAP as described in the paper shall facilitate price risk management apart from improving the efficiency of price discovery.

Originality/value

To the best of the knowledge, this is the first study considering mandi, spot and futures prices in the price discovery process in India. In addition, this study found the role of mandi markets in serving the economic function of price discovery and price risk management. Hence, suggests for policy intervention for Indian agricultural commodities to manage price risk.

Details

Journal of Modelling in Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 19 July 2021

Taicir Mezghani, Fatma Ben Hamadou and Mouna Boujelbène Abbes

The aim of this study was to investigate the dynamic network connectedness between stock markets and commodity futures and its implications on hedging strategies…

Abstract

Purpose

The aim of this study was to investigate the dynamic network connectedness between stock markets and commodity futures and its implications on hedging strategies. Specifically, the authors studied the impact of the 2014 oil price drop and coronavirus disease 2019 (COVID-19) pandemic on risk spillovers and portfolio allocation among stock markets (United States (SP500), China (SSEC), Japan (Nikkei 225), France (CAC40) and Germany (DAX)) and commodities (oil and gold).

Design/methodology/approach

In this study, the authors used the Baba, Engle, Kraft and Kroner–generalized autoregressive conditional heteroskedasticity (BEKK–GARCH) model to estimate shock transmission among the five financial markets and the two commodities. The authors rely on Diebold and Yılmaz (2014, 2015) methodology to construct network-associated measures.

Findings

Relying on the BEKK–GARCH, the authors found that the recent health crisis of COVID-19 intensified the volatility spillovers among stock markets and commodities. Using the dynamic network connectedness, the authors showed that at the 2014 oil price drop and the COVID-19 pandemic shock, the Nikkei225 moderated the transmission of volatility to the majority of markets. During the COVID-19 pandemic, the commodity markets are a net receiver of volatility shocks from stock markets. In addition, the SP500 stock market dominates the network connectedness dynamic during the COVID-19 pandemic, while DAX index is the weakest risk transmitter. Regarding the portfolio allocation and hedging strategies, the study showed that the oil market is the most vulnerable and risky as it was heavily affected by the two crises. The results show that gold is a hedging tool during turmoil periods.

Originality/value

This study contributes to knowledge in this area by improving our understanding of the influence of fluctuations in oil prices on the dynamics of the volatility connection between stock markets and commodities during the COVID-19 pandemic shock. The study’s findings provide more implications regarding portfolio management and hedging strategies that could help investors optimize their portfolios.

Details

Asia-Pacific Journal of Business Administration, vol. 13 no. 4
Type: Research Article
ISSN: 1757-4323

Keywords

Article
Publication date: 31 May 2013

Brajesh Kumar and Ajay Pandey

In this paper, the authors aim to investigate the short‐run as well as long‐run market efficiency of Indian commodity futures markets using different asset pricing models…

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Abstract

Purpose

In this paper, the authors aim to investigate the short‐run as well as long‐run market efficiency of Indian commodity futures markets using different asset pricing models. Four agricultural (soybean, corn, castor seed and guar seed) and seven non‐agricultural (gold, silver, aluminium, copper, zinc, crude oil and natural gas) commodities have been tested for market efficiency and unbiasedness.

Design/methodology/approach

The long‐run market efficiency and unbiasedness is tested using Johansen cointegration procedure while allowing for constant risk premium. Short‐run price dynamics is investigated with constant and time varying risk premium. Short‐run price dynamics with constant risk premium is modeled with ECM model and short‐run price dynamics with time varying risk premium is modeled using ECM‐GARCH in‐Mean framework.

Findings

As far as long‐run efficiency is concerned, the authors find that near month futures prices of most of the commodities are cointegrated with the spot prices. The cointegration relationship is not found for the next to near months futures contracts, where futures trading volume is low. The authors find support for the hypothesis that thinly traded contracts fail to forecast future spot prices and are inefficient. The unbiasedness hypothesis is rejected for most of the commodities. It is also found that for all commodities, some inefficiency exists in the short run. The authors do not find support of time varying risk premium in Indian commodity market context.

Originality/value

In context of Indian commodity futures markets, probably this is the first study which explores the short‐run market efficiency of futures markets in time varying risk premium framework. This paper also links trading activity of Indian commodity futures markets with market efficiency.

Details

Journal of Indian Business Research, vol. 5 no. 2
Type: Research Article
ISSN: 1755-4195

Keywords

Article
Publication date: 22 November 2022

Chao Liu, Wei Zhang, Qiwei Xie and Chao Wang

This study aims to systematically reveal the complex interaction between uncertainty and the international commodity market (CRB).

Abstract

Purpose

This study aims to systematically reveal the complex interaction between uncertainty and the international commodity market (CRB).

Design/methodology/approach

A composite uncertainty index and five categorical uncertainty indices, together with wavelet analysis and detrended cross-correlation analysis, were used. First, in the time-frequency domain, the coherency and lead-lag relationship between uncertainty and the commodity markets were investigated. Furthermore, the transmission direction of the cross-correlation over different lag periods and asymmetry in this cross-correlation under different trends were identified.

Findings

First, there is significant coherency between uncertainties and CRB mainly in the short and medium terms, with natural disaster and public health uncertainties tending to lead CRB. Second, uncertainty impacts CRB more markedly over shorter lag periods, whereas the impact of CRB on uncertainty gradually increases with longer lag periods. Third, the cross-correlation is asymmetric and multifractal under different trends. Finally, from the perspective of lag periods and trends, the interaction of uncertainty with the Chinese commodity market is significantly different from its interaction with CRB.

Originality/value

First, this study comprehensively constructs a composite uncertainty index based on five types of uncertainty. Second, this study provides a scientific perspective on examining the core and diverse interactions between uncertainty and CRB, as achieved by investigating the interactions of CRB with five categorical and composite uncertainties. Third, this study provides a new research framework to enable multiscale analysis of the complex interaction between uncertainty and the commodity markets.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 4 May 2022

Palak Dewan and Khushdeep Dharni

The study examines herding in the Indian stock and commodity futures market including agricultural, metal and energy commodities. Herding is studied under various market

Abstract

Purpose

The study examines herding in the Indian stock and commodity futures market including agricultural, metal and energy commodities. Herding is studied under various market conditions: rising and declining, high and low volatility. The study also examines spillover effects of herding.

Design/methodology/approach

The study adapts the cross-sectional absolute deviation model given by Chang et al. (2000) to examine herding in Indian stock and commodity futures markets.

Findings

The results of the study indicate absence of herding among commodity futures under all market conditions except for the declining market where herding is present among energy futures. The investors investing in agricultural and energy commodities have a higher tendency to herd during high volatility days as compared to low volatility days. Further, the study of herding spillover effects indicates that the price fluctuations in metal commodities affect herding in agricultural and energy commodities.

Research limitations/implications

The results can help market participants to diversify the risk by investing in agricultural, metal and energy futures along with the stocks.

Originality/value

Majority of the previous studies explore herding among stocks and ignore commodities especially agricultural commodities. This study attempts to fill the gap by studying herding among various commodity futures. To the best of our knowledge this is the first study to explore herding spillover effects in the Indian stock and commodity futures market.

Details

Journal of Agribusiness in Developing and Emerging Economies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-0839

Keywords

Article
Publication date: 2 June 2021

Saji Thazhugal Govindan Nair

This paper aims to investigate price responses and volatility spillovers between commodity spot and futures markets. The study ultimately seeks the evidence-based claims…

Abstract

Purpose

This paper aims to investigate price responses and volatility spillovers between commodity spot and futures markets. The study ultimately seeks the evidence-based claims on the efficiency of the long run and short run horizontal price transmissions from futures markets to spot markets.

Design/methodology/approach

This study used the most recent daily price series of pepper, cardamom and rubber, during the period 2004–2019, use “cointegration-ECM-GARCH framework” and verify the persisting validity of the “expectancy theory” of commodity futures pricing.

Findings

The results offer overwhelming evidence of futures market dominance in the price discoveries and volatility spillovers in spot markets. However, this paper finds asymmetric responses between cash and futures prices across markets. The hedging efficiency of futures contracts is commodities specific’ where spices futures are more efficient than the rubber futures.

Practical implications

The study passes on vital information to the producers and traders of spices and rubber who have a potential interest in the use of futures contracts to make profits from arbitrage between futures and cash markets.

Originality/value

The paper is unique in terms of understanding asymmetric price linkages in markets for plantation crops.

Details

Indian Growth and Development Review, vol. 14 no. 2
Type: Research Article
ISSN: 1753-8254

Keywords

Article
Publication date: 27 September 2021

Manogna RL and Aswini Kumar Mishra

The phenomenon known as financialization of commodities, arising from the speculation in commodity derivatives market, has raised serious concerns in the recent past. This…

199

Abstract

Purpose

The phenomenon known as financialization of commodities, arising from the speculation in commodity derivatives market, has raised serious concerns in the recent past. This has prompted distortion in agricultural commodity prices driving them away from rational levels of supply and demand shocks. In the backdrop of financialized commodities leading to increase in price of agricultural products and their interaction with equity markets, the authors examine the investment of institutional investors in impacting the agricultural returns. The paper aims to focus on the financial mechanism that drives extreme values and the mean of agricultural returns.

Design/methodology/approach

The authors employ the Threshold AutoRegressive Quantile (TQAR) methodology to find evidence of linkages between the Indian agricultural and equity markets from January 2010 to May 2020 consistent with the rise in inflows of institutional investors in agricultural markets.

Findings

The results reveal that the investors impact the agricultural commodity markets strongly when the composite commodity index value (COMDEX) is low. Additionally, in the lower extreme quantiles (0.25) of agricultural returns, the integration between the equity index and agricultural returns is found to be highly significant compared to insignificant values in the higher quantiles (0.75 and 0.95) in both the regimes. The results suggest that low values of agricultural commodities are more closely linked to equity indices when composite commodity index value is low. This implies that, at the lower quantiles of COMDEX return (bad day), the investors move to the stock market. In that way, the commodity index returns are seen to be as a strong channel for the financialization of Indian agricultural commodities and suggesting potential involvement of investors during those regime.

Research limitations/implications

Regulators need to anticipate the price fluctuations in spot and futures markets. Investors in commodity markets need to strengthen risk awareness to carry out portfolio strategies.

Practical implications

From policy perspective, it is of pivotal importance to enhance the understanding of the financialization of agricultural products. The findings provide reference measures to stabilize the commodity markets, alleviate price distortions and carry out further evidence of price discovery and risk management in Indian commodity markets.

Originality/value

To the best of the authors’ knowledge, this study is the first to highlight the potential influence of financial markets on the financialization of agricultural commodities in an emerging economy like India.

Details

International Journal of Social Economics, vol. 49 no. 1
Type: Research Article
ISSN: 0306-8293

Keywords

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