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The purpose of this paper is to ascertain the possible consequences of ban on futures trading of agriculture commodities in India by examining three critical issues: first, the author explores whether price discovery dominance changes between futures and spot in the pre-ban and post-relaunch phase both in the long run and short run. Second, the author examines the impact of ban and relaunch of futures trading on its underlying spot volatility for five sample cases of agriculture commodities (Wheat, Sugar, Soya Refined Oil, Rubber and Chana) using both parametric and non-parametric tests. Third, the author revisits the destabilization hypothesis in the light of ban on futures trading by examining the impact of unexpected component of liquidity of futures on spot volatility.

The author uses widely adopted methodology of co-integration to examine long-run relationship between spot and futures, while the short-run relationship is investigated using vector error correction model (VECM) and Granger causality to test price discovery in the pre-ban and post-relaunch phases. The second objective is explored using a combination of parametric and non-parametric tests such as Welch one-way ANOVA and Kruskal–Wallis test, respectively, to gauge the impact of ban on futures trading on spot volatility along with post hoc tests to investigate pairwise comparison of spot volatility among three phases (pre-ban, ban and post-relaunch) using Dunn Test. In addition, extensive robustness test is undertaken by adopting augmented E-GARCH model to ascertain the impact of ban and relaunch of futures trading on spot volatility. The third objective is investigated using Granger causality test between spot volatility and unexpected component of liquidity of futures estimated using Hodrick and Prescott (HP) filter to re-visit the destabilization hypothesis.

The author found extensive evidence for the dominance of futures market in the price discovery of agriculture commodities both in the pre-ban and post-relaunch phases in India. The ban on futures trading is found to have a destabilizing impact on spot volatility as evident from the findings of Wheat, Sugar and Rubber. In addition, it is observed that spot volatility was highest during the ban phase as compared to the pre-ban and post-relaunch phases for all four commodities barring Chana. The author found that destabilisation hypothesis holds true during the pre ban phase, while weakening of destabilization hypothesis is observed in the post-relaunch phase as unexpected futures liquidity has no role in driving the spot volatility.

This study is a novel attempt to empirically examine the potential impact of ban and relaunch of futures trading of agriculture commodities on two key market quality dimensions – price discovery and spot volatility. In addition, destabilization hypothesis is revisited to investigate the impact of futures trading on spot volatility during the pre-ban and post-relaunch period.

The global energy market has been facing lower prices of crude oil in recent years. Lower fuel price leads to lower transport cost and cheaper agricultural inputs (such as pesticides and chemical fertilizer), resulting in lower prices of agricultural commodities in the international markets. On the other hand, lower global oil price reduces the oil revenues of oil exporting countries, resulting in a decrease in government expenditures. Therefore, the purpose of this study is to examine the impacts of lower global oil and agricultural commodity prices and government expenditure on the entire economy and poverty level of Malaysia.

This study used a computable general equilibrium model (CGE) to investigate four simulation scenarios based on the latest Malaysia’s input-output table belonging to 2010. The first scenario is a 30 per cent fall in the export and import prices of agricultural commodity prices, while the second is a 50 per cent decline in the export and import prices of crude oil, and the third combines them. In the fourth scenario, government operating expenditure declines by 4 per cent because of the fall in government’s oil revenues as a result of the decline in global oil prices.

The simulation results suggest that lower international oil price decreases real gross domestic product (GDP) and investment in Malaysia and influences positively the output and employment of some agriculture sectors. However, lower agricultural commodity price increases real GDP and investment in the country and negatively influences the output, employment and exports of all agriculture sectors. The decline in government expenditures also increases the output and the employment in the economy, whereas it decreases household consumption. In conclusion, results show that the agriculture sector losses from the current decline in international agricultural commodity prices, while it benefits from lower oil and government expenditure.

The main contribution of this study is comparing the impacts of recent falls in global oil and agricultural prices on the entire economy and agriculture sector of Malaysia. Investigating the impacts of these issues on the poverty level of Malaysian households is another contribution to the study. Another contribution is analyzing the impact of a reduction in government expenditures because of the decline in global oil price on the economy and welfare of Malaysia. Therefore, this study makes a useful contribution to the small literature of the topic.

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.

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.

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.

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.

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

Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly wholesale price index of green grams in the Chinese market. The index covers a ten-year period, from January 1, 2010, to January 3, 2020, and has significant economic implications.

In order to address the nonlinear patterns present in the price time series, we investigate the nonlinear auto-regressive neural network as the forecast model. This modeling technique is able to combine a variety of basic nonlinear functions to approximate more complex nonlinear characteristics. Specifically, we examine prediction performance that corresponds to several configurations across data splitting ratios, hidden neuron and delay counts, and model estimation approaches.

Our model turns out to be rather simple and yields forecasts with good stability and accuracy. Relative root mean square errors throughout training, validation and testing are specifically 4.34, 4.71 and 3.98%, respectively. The results of benchmark research show that the neural network produces statistically considerably better performance when compared to other machine learning models and classic time-series econometric methods.

Utilizing our findings as independent technical price forecasts would be one use. Alternatively, policy research and fresh insights into price patterns might be achieved by combining them with other (basic) prediction outputs.

The study investigates the inter-linkages between geopolitical risk (GPR) and food price (FP).

By employing the bootstrap full- and sub-sample rolling-window Granger causality tests.

The empirical results show that there is a time-varying bidirectional causality between GPR and FP. High GPR leads to a rise in FP, suggesting that geopolitical events usually may disrupt supply and demand conditions in food markets, and even trigger global food crises. However, the negative effect of GPR on FP does not support this view in certain periods. This is mainly because GPR is also related to the global economic situation and oil price, which together have impacts on the food market. These results cannot always be supported by the inter-temporal capital asset pricing model, which states that GPR affects FP in a positive manner. Conversely, there is a positive impact of FP on GPR, indicating that the food market is an effective tool that can reflect global geopolitical environment.

In the context of the Russia–Ukraine conflict, these analyses can assist investors and policymakers to understand the sensitivity of FP to GPR. Also, it will provide significant revelations for governments to attach importance to the role of food price information in predicting geopolitical events, thus contributing to a more stable international environment.

Considering the importance of Russia and Ukraine in agriculture, the authors quantify the potential impact of the Russia–Ukraine conflict on food output, trade, prices and food security for the world.

The authors mainly use the quantitative and structural multi-country and multi-sector general equilibrium trade model to analyze the potential impacts of the conflict on the global food trade pattern and security.

First, the authors found that the conflict would lead to soaring agricultural prices, decreasing trade volume and severe food insecurity especially for countries that rely heavily on grain imports from Ukraine and Russia, such as Egypt and Turkey. Second, major production countries such as the United States and Canada may even benefit from the conflict. Third, restrictions on upstream energy and fertilizer will amplify the negative effects of food insecurity.

This study analyzed the effect of Russia–Ukraine conflict on global food security based on sector linkages and the quantitative general equilibrium trade framework. With a clearer demonstration of the influence about the inherent mechanism based on fewer parameters compared with traditional Global Trade Analysis Project (GTAP) models, the authors showed integrated impacts of the conflict on food output, trade, prices and welfare across sectors and countries.

The purpose of this paper is to examine the market impacts of US biofuels and biofuel policies.

Two methods of analysis are employed. The first method looks back in time and estimates what US crop prices would have been during the 2005 to 2009 marketing years under two scenarios. The second method of analysis is forward looking and examines the market impacts of the blender tax credit and mandate on the distribution of prices in the 2011 calendar and marketing year.

The results developed in the previous two sections show that US ethanol policies modestly increased maize prices from 2006 to 2009 and that market impacts of the policies will be larger under tighter market conditions.

More flexible US biofuel policy including removing the blenders tax credit, which does not help US biofuel industry as long as the mandates are in place, and relaxing blending mandates when feedstock supplies are low.

This report makes three contributions to understanding the extent to which US biofuel policies contribute to higher agricultural and food prices. First, estimates of the impact of US ethanol policies on crop and food prices reveal that the impacts of the subsidies were quite modest. The second contribution is to provide estimates of the impact on agricultural commodity prices and food prices from market‐driven expansion of ethanol. The final contribution of this report is improved insight into how current US biofuel policies are expected to affect crop prices in the near future.

The purpose of this paper is to examine the causal relationship between the copper price dynamics and economic growth in Zambia over the period from 1995 to 2015.

The study uses a data set assembled from five difference sources: the heritage foundation; the London metal exchange index; the Penn World Tables version 9.0; the total economy database; and the World Bank Development Indicators. The paper employs the Bayesian Model Averaging (BMA) approach as the estimation technique.

The estimates demonstrate that there exists a positive and significant relationship between movements in copper prices and economic growth in Zambia. The study draws policy implications from these findings.

This study is limited to the period from 1995 to 2015, this is due to lack of data on the country’s institutional indicators, trade openness and the real exchange rate.

There have been calls to diversify the economy of Zambia due to the recurring chaotic events, which are often induced by over-dependence on copper exports. Thus, the study findings will be useful to academia, policy makers and stakeholders with vested interest in the economy of Zambia.

To the best of the author’s knowledge, this is the first empirical study to investigate the causal relationship that exists between copper prices and economic growth in Zambia. The existing empirical studies in the domain have devoted their attention on establishing the relationship between commodity price movements and exchange rates in Zambia.

The purpose of this study is to examine empirically the conditional correlation between the major US indices (S&P500 index and Dow Jones Industrial index) and three selected meat commodities as: Feeder Cattle, Leen Hogs and Live Cattle during the period from July 22, 2010 to June 30, 2017.

In this study, the authors use for the first time the GARCH-DECO (1,1) to examine empirically the conditional nexus between the major US indices (S&P500 index and Dow Jones Industrial index) and three selected meat commodities as; Feeder Cattle, Leen Hogs and Live Cattle during the period from July 22, 2010 to June 30, 2017.

From the empirical findings, the authors conclude the existence of a highly significance of conditional heteroscedasticity parameters can demonstrate us to distinguish the nature of the volatility dependency between S&P500 index and Dow Jones Industrial index and three selected meat commodities indices.

This can find clear the significance of relationship in the process of financialization of the major US index and meat commodities indices in the case of this paper.

Guar Seed crop is ruling the Indian International business mainly due to its application as a drilling fluid in shale energy industry concentrated in the USA. One of the allegations against futures market is its possible role in increasing the volatility of underlying physical market prices. Suspension of guar seed futures contract in 2012 at National Commodity Derivatives Exchange of India (NCDEX)-India, has reignited the controversy and raised an alarm bell to peek into obscure world of Indian commodity derivatives market. Against the backdrop of fiasco in guar futures trading, the purpose of this paper is to investigate whether sudden surge in futures trading volume leads to increase in the volatility of spot market prices.

Guar seed spot returns volatility is modeled as a GARCH (1, 1) process. Futures trading volume and open interest are segregated into expected and unexpected components. The data are analyzed from 2004 to 2011 using Augmented GARCH model to study the contemporaneous relationship between spot volatility and unexpected futures trading activity and Granger Causality test for examining the dynamic relationship between them and ascertaining causality.

Augmented GARCH model reports positive relationship between unexpected futures trading volume (UTV) and spot returns volatility, and, Granger Causality flows from UTV to spot volatility. Therefore, when the level of futures trading volume increases unexpectedly, the volatility of spot prices increases pointing toward the destabilizing impact of futures trading. However, hedger’s activity, represented by open interest is not seen to have any causal/destabilizing impact on spot price volatility of guar seed.

The study provides empirical evidence to support the concern of regulators, genuine hedgers and other traders about the presence of excessive speculation and market manipulations perpetrated through futures market that is disturbing the underlying physical market instead of strengthening it by aiding in price discovery and risk mitigation.

There are very few studies which have empirically investigated the temporal relation between volume and volatility in Indian agricultural commodity markets. With guar seed as a special case the present study investigates statistically the impact of futures trading on spot price volatility. In light of the findings of the study, the curb imposed on guar seed futures trading in 2012 was justified.