Agricultural Commodity Futures Research Articles

Statistics Show Value in Old‐School Crop Condition Reports

Statistics Show Value in Old‐School Crop Condition Reports

Price Discovery in the Presence of Embedded Location Options: The Evidence from Chana Contracts in India

The presence of embedded location options in agricultural commodity futures contracts allows for several additional deliverable locations in addition to the reference location for the delivery of the underlying asset using location specific adjustments to futures settlement prices. Price discovery contribution assessment in this context needs to be done simultaneously across futures and cash markets in all these deliverable locations in contrast to present bivariate studies in the Indian context, which only consider futures and the cash market at reference location. We assess price discovery contributions across all the deliverable cash markets and the most liquid futures contract for Chana (Gram/Chickpea) in India. We find that while futures lead price discovery as expected, the cash market at the reference location plays almost no role in price discovery with cash markets at additional deliverable locations playing a larger than expected role. We interpret these results as arising from large values of location options for Chana due to inappropriate specifications of deliverable asset locations and associated premiums and discounts. These results provide evidence that exchanges and regulators need to monitor option values and optimize delivery specifications of futures contracts so that they perform their functions of price discovery and risk transfer well.

Dynamic correlation between crude oil and agricultural futures markets

AbstractIn recent years, the relationship between agricultural commodities and crude oil has become increasingly close with the promotion of biofuel policies. This study examines the dynamic correlation between global crude oil futures and seven agricultural commodity futures by applying the consistent dynamic conditional correlation and dynamic equicorrelation models. The empirical results show that the dynamic correlation between the global crude oil futures market and China's agricultural futures market is weak compared to the global agricultural futures market. In particular, soybean oil has the strongest correlation with crude oil, while Dalian Commodity Exchange (DCE) corn and Zhengzhou Commodity Exchange wheat have the weakest correlation with crude oil. There is an indirect linkage between crude oil futures and DCE soybean meal and DCE soybean oil. Moreover, the dynamic correlation between crude oil and agricultural commodities increased during the financial crisis, the novel coronavirus (COVID‐19) epidemic, and the crude oil crash crisis. Brent crude oil has a stronger co‐movement with China's agricultural commodities than West Texas Intermediate crude oil and can better hedge the risk of agricultural commodities. The findings of this study provide some insights into the contagion risk management of crude oil futures and agricultural futures markets.

Long‐short speculator sentiment in agricultural commodity markets

AbstractThis paper tests the hypothesis that long‐short speculators are able to generate short‐term investment returns based on their sentiment for 12 agricultural commodity futures. For this purpose, we dynamically model the equidirectional trading of long and short commodity futures of long‐short speculators as a proxy for their market sentiment. We find evidence that the sentiment period returns are considerably positive and differ significantly from neutral sentiment periods for all commodities, which underlines the sentiment's relevance. In line with the empirical literature, we can reject the argument of price manipulation as the price continues to develop into the direction of the sentiment period although long‐short speculators trade non‐directionally in the following. We rather indicate the existence of a short‐term time‐series momentum effect, which can be robustly identified without the requirement to define an external model parameter. From the superior sentiment‐based momentum returns, we conclude that long‐short speculators have valuable, exclusive information, which cannot be replicated by observing their trading activity with a time lag of eight trading days. We also find that a sentiment‐based momentum strategy generates significantly higher returns than the long‐short speculators have realised in the 15‐year sample period which we attribute to the complexity of the long‐short speculators' investment strategies.

Optimizing Hedging Effectiveness of Indian Agricultural Commodity Futures: A Simulation Approach

Optimizing Hedging Effectiveness of Indian Agricultural Commodity Futures: A Simulation Approach

The impact of embedded location options on price discovery of agricultural futures contracts – the evidence from the Chana contract

PurposeEmbedded options can create asymmetries in information impounded by cash and futures markets, causing errors in price discovery estimation. This paper aims to investigate the impact of embedded location options on measures of price discovery.Design/methodology/approachVarious price discovery metrics are computed using observed futures prices that contain embedded location options and cash prices for Chana. Prices of a futures contract that contains no options using observed futures prices and estimates of location option value are synthesized. The price discovery measures are recomputed using synthetic option-adjusted futures contract prices and cash prices, and changes in these measures are attributed to the impact of the embedded location option.FindingsIf the presence of the location option is ignored, futures appear to dominate price discovery. Once the location option is adjusted for, cash markets are found to dominate price discovery.Research limitations/implicationsThe lack of complete time-series data from the exchange for multiple commodities allows only limited empirical evidence for generalizing conclusions.Practical implicationsThis paper highlights that regulators, exchanges and policymakers in India need to revisit delivery specifications of agricultural commodity futures contracts to enhance their utility from a price discovery perspective.Originality/valueThis work shows that ignoring the presence of embedded options can cause significant errors in price discovery assessment of agricultural futures contracts, particularly in heterogenous cash markets.

Forecasting the volatility of agricultural commodity futures: The role of co‐volatility and oil volatility

AbstractWe forecast the realized volatilities of China's agricultural commodity futures (corn, cotton, palm, wheat, and soybean) using a set of multivariate heterogeneous autoregressive (MHAR) models. We consider different error structures to capture the co‐movement of volatility (co‐volatility) between commodity futures to obtain out‐of‐sample forecasts of the realized volatilities of agricultural commodity futures at daily, weekly, and monthly forecast horizons. We also consider global oil volatility as an additional exogenous predictor and assess forecast precision based on both statistical and economic value measures. The results show that the MHAR model with a co‐volatility error structure is superior in predicting the volatility of commodity futures. The most accurate predictions are of corn, cotton, and wheat futures volatility. Interestingly, for all the commodities, the forecasting accuracy noticeably improves as the forecast horizon increases. However, from an investment perspective, the highest economic value is gained from medium‐horizon forecasts, and the economic value of forecasts is highest for less risk‐averse investors.

The effect of temperature anomaly and macroeconomic fundamentals on agricultural commodity futures returns

This paper is the first to examine the dynamic impact of temperature anomaly and macroeconomic fundamentals on agricultural commodity futures returns. Using a quantile regression approach, we report that temperature anomaly exerts a significant negative (positive) impact on returns of soybean, corn, cotton, and coffee (soybean, corn, and cocoa) futures in extreme bearish and bullish market conditions. Moreover, agricultural commodity futures returns appear to positively respond to aggregate stock returns and negatively influenced by exchange rate changes. However, such results vary across quantiles. We also report that economic activities and various uncertainty measures do not have a strong impact on the returns of agricultural commodity futures. Our study suggests that an adjustment in risk evaluation encompassing weather shocks would benefit portfolio management.

Competence and efficacy of commodity futures market: Dissection of price discovery, volatility, and hedging

The paper is an attempt to assess the Indian agricultural commodity futures market in terms of price discovery, hedging efficiency, and volatility. Cointegration test, Granger causality test, and vector error correction (VEC) model, ordinary least squares (OLS) regression, exponential generalised autoregressive conditional heteroskedasticity (EGARCH) model, value-at- risk (VaR) model are employed to achieve the objectives of the study. It is observed that the spot market leads the futures market. The lead-lag relationship varies from commodity to commodity. Additionally, downside risk exists in both the markets, and volatility is transmitted from the spot market to the futures market. The agricultural commodity futures market is found to lack hedging efficiency.

The Optimization of Bayesian Extreme Value: Empirical Evidence for the Agricultural Commodities in the US

Bayesian extreme value analysis was used to forecast the optimal point in agricultural commodity futures prices in the United States for cocoa, coffee, corn, soybeans and wheat. Data were collected daily between 2000 and 2020. The estimation of extreme value can be empirically interpreted as representing crises or unusual time series trends, while the extreme optimal point is useful for investors and agriculturists to make decisions and better understand agricultural commodities future prices warning levels. Results from the Non-stationary Extreme Value Analysis (NEVA) software package using Bayesian inference and the Newton-optimal methods provided optimal interval values. These indicated extreme maximum points of future prices to inform investors and agriculturists to sell the contract and product before the commodity prices dropped to the next local minimum values. Thus, agriculturists can use this information as an advanced warming of alarming points of agricultural commodity prices to predict the efficient quantity of their agricultural product to sell, with better ways to manage this risk.

An empirical study on the regulated Chinese agricultural commodity futures market based on skew Ornstein-Uhlenbeck model

This paper describes the regulated agricultural commodity futures market of China, focusing on six actively traded futures: corn, strong gluten wheat, No. 1 soybean, soymeal, cotton, and white sugar. A novel skew Ornstein-Uhlenbeck model is employed to characterize price dynamics with government controls. The empirical analysis reveals significant skew phenomena in these six futures and indicates that the price dynamics are influenced by state policy. The observed skew phenomena are most notable in grain futures, with relatively weaker, but statistically significant, evidence of skew phenomena in oilseed and soft futures markets. In addition, generalized quasi-likelihood ratio tests show that the skew Ornstein-Uhlenbeck model is superior to the Ornstein-Uhlenbeck model.

The macroeconomic variables impact on commodity futures volatility: A study on Indian markets

The research investigated the impact of macroeconomic variables on the volatility of the commodity futures market in India (together with oil futures, agricultural commodity futures and metal futur...

Price discovery in chinese agricultural futures markets: A comprehensive look

AbstractThis study investigates price discovery performance for the 11 most traded agricultural commodity futures in China, proposing an improved recursive cointegration analysis. Despite a relatively short trading history and being subject to various policy interventions, China's agricultural futures markets generally play a more dominant role in the price discovery process as the markets become mature, even with further allowance for time variations and regional variations in the price discovery process. Additional analysis reveals various determinants of the contribution of futures versus local cash market prices in the price discovery process. There may also be seriously misleading inferences drawn from using nearby futures data in China.

Heterogeneity of Cash Markets at Physical Delivery Points and the Hedging Effectiveness of Agricultural Commodity Futures in India – Lessons for Contract Optimization.

Agricultural commodity futures in India are settled by physical delivery and the seller can choose the location of delivery from a list described in the contract specifications. Cash markets at these locations represent the deliverable basket for the futures contract and are the underlying assets for the delivery options granted to the seller by virtue of contract design. These cash markets are generally heterogenous. This paper studies the impact of heterogeneity of the underlying cash markets in different locations on the hedging effectiveness of the associated futures contract. The hedging effectiveness of cottonseed oilcake and soybean futures is regressed against several variables that represent heterogeneity of the underlying cash markets using ridge regression. We find that in general, the greater the heterogeneity, the poorer the hedging effectiveness of the contract. This paper is unique in that it provides a framework for guidance for contract designers at exchanges and regulators who will find this research useful in optimizing delivery specifications for agricultural futures contracts. This is especially important given the declining volumes in Indian agricultural commodity futures.

Risk contagions between global oil markets and China’s agricultural commodity markets under structural breaks

ABSTRACT This article investigates the linear and non-linear dependence structures of risk contagions between global crude oil futures markets and China’s agricultural futures markets based on a regime switching skew-normal (RSSN) model. We examine the oil-agriculture relationships and identify the contagion channels under the calm and turbulent oil market conditions. The directions of contagions are further identified with the directed acyclic graph (DAG) from the linear non-Gaussian acyclic models algorithm. The empirical results of contagions tests show the significance of correlation and covariance contagions across the oil and agriculture futures returns, especially under the turbulent oil market condition. The breaks in the variances through the moment-based break tests are found to be most significant, followed by the mean and skewness breaks. In addition, the DAG results support the volatility contagions from world oil future markets to China’s agricultural commodity futures markets. Our empirical results have important policy implications for the government to take effective measures to stabilize China’s commodity market and promote the development of alternative energy in China, as well as for market participants to best manage the market risks.

Algorithmic quoting, trading, and market quality in agricultural commodity futures markets

ABSTRACT This paper investigates the effect of algorithmic trading activity, as measured by quoting, on the corn, soybean, and live cattle commodity futures market quality. Using the CME’s limit-order-book data and a heteroscedasticity-based identification approach, we find more intensive algorithmic quoting (AQ) is beneficial to multiple dimensions of market quality. AQ improves pricing efficiency and mitigates short-term volatility, but its effects on liquidity costs are somewhat mixed. Increased AQ significantly narrows effective spreads in the corn and soybean markets, but not in the less traded live cattle futures market. The narrowing in effective spreads emerges from a reduction in adverse selection costs as more informed traders lose their market advantage. There also is evidence that liquidity provider revenues increase with heightened AQ activity in the corn futures market, albeit the effect is not statistically significant in the soybean and live cattle futures markets. The increased revenue points to a tradeoff between the dimensions of market quality, and the need for continued assessment and monitoring of algorithmic trading activity.

The impact of the change in USDA announcement release procedures on agricultural commodity futures

In August 2018, the US Department of Agriculture (USDA) ceased its practice of early media access during lockup, in which the news media have access to crop and livestock reports ahead of scheduled announcements. News media no longer have a 90-min window to digest and write custom reports and are now subject to the same information distribution rules as the public. We examine the impact of this regulatory change on the trading of agricultural commodity futures. We assess changes in market quality (e.g., liquidity, volatility, information asymmetry, and high-frequency trading activity) around news announcements before and after the regulatory change. Although the majority of our market quality proxies react to USDA news releases, they are not statistically different before and after the regulatory change. The overall results show that ending the practice of early media access lockup does not have a significant economic impact on agricultural futures trading around USDA news releases.

Multivariate correlation analysis of agricultural futures and spot markets based on multifractal statistical methods

Agricultural commodity futures are the earliest listed futures in the world. The rapid development of their markets has greatly affected the world agricultural production and circulation. Thereby, the volatility characteristics of agricultural futures markets and the cross-correlations between the futures and spot markets have attracted extensive attention from investors, regulators and researchers. Two new fractal statistical methods are firstly developed in this paper. Then, from the perspective of system theory, some multifractal analysis methods, including the two newly developed methods, are used to study the autocorrelation, cross-correlation and coupling correlation for the return series of five agricultural futures and their corresponding spot varieties in CBOT. The empirical results show that the autocorrelations and cross-correlations of both the futures and spot systems are multifractal and present different dynamic fluctuation characteristics at different time scales. The long-term co-movement between the two systems is not strong and the overall risk spillover effect is not obvious. In addition, the coupling cross-correlations are found between the corresponding components, but the strengths are distinct due to the different influences of long-range correlations and fat-tailed distributions.

O risco de informação assimétrica sobre a liquidez dos contratos futuros de commodities agrícolas

O objetivo deste estudo é analisar o efeito do risco de assimetria informacional na liquidez dos contratos futuros de commodities agrícolas negociados pela B3. Para tanto, escolheu-se como amostra as negociações intradiárias das commodities Boi Gordo, Café Arábica, Milho e Soja, no período de 01 de dezembro de 2018 a 30 de novembro de 2019. A analise foi realizada por meio de um modelo de dados em painel, utilizando-se como proxy para liquidez, o spread, para a probabilidade de presença de assimetria informacional nas negociações a VPIN e, como variáveis de controle, o número de negócios, o volume negociado e a volatilidade. Pelo modelo estimado, demostrou-se que as variáveis consideradas são capazes de explicar 43,08% da variação do spread. Além disso, os resultados mostraram uma relação inversa entre o risco de se negociar com assimetria informacional e a liquidez de mercado, divergindo dos resultados encontrados na literatura nacional e internacional.

COMMODITY FUTURE MARKET IN INDIA: A LITERATURE REVIEW ON PRICE DISCOVERY OF AGRICULTURAL COMMODITY

The purpose of this paper is to know about the Agricultural commodity futures market in India based on these few empirical papers have been selected related to the agricultural commodity future, The selected period for this study is 2001 – 2019. These review paper has been categorized into two sections: Pre – global crisis and Post – global crisis. The study discusses the price discovery before and after crisis along with the market efficiency, informational flow, and also the interrelation between the spot and futures market.