Analysing Cause & Effect Lag Relationship between Spot & Future Returns of Agro Commodities

Derivatives market help in reducing volatility in spot markets due to increase in the information flow from future market to the spot market. Also, it attracts the speculators to the spot market and take alternate positions at lower cost. This helps in reducing volatility in spot markets. Derivative markets perform many functions like Price Discovery, reducing volatility spillover, hedging and risk management. The objective of the study was identified to study the causal or lead and lag relationship and analyse Cause & Effect Lag Relationship between Spot & Future Returns of sampled Agro commodities. Ten agricultural commodities frequently traded on NCDEX i.e. Mustard Seed, Refined Soy Oil, Crude Sunflower Oil, Refined Castor Oil, Groundnut, Raw Yellow Peas, Moong, Bajra, Paddy (Basmati) & Maize Feed were considered in the study. Sampled commodities were selected based on March, 2018 observed trading volumes from two major commodity groups of NCDEX, namely Cereals & Spices and Oil & Oil seeds and duration of the study was for 6 years i.e. April 2018 to August 2024. Vector Auto Regression (VAR) Model: VAR model is used to study the causal or lead and lag relationship between spot and future market of the commodities. The Block exogeneity Granger’s causality test along with impulse response function and variance decomposition variance estimates were analyzed. The causality method is applied to the different selected commodities. During the period of study Spot and future prices of all the agro commodities showed fluctuations. Mean spot prices were greater than mean future prices for all agri-commodities except Mustard Seed, Groundnut and Paddy (Basmati) during the period of study. ADF Unit root test showed that time series was not stationary at level 0. However, the time series became stationary at first log transformation for all 10 commodities. There exists high positive significant correlation between the Agri spot and future commodity prices which showed that during the period of study they were moving in the same direction. There exists Bi-directional causality between spot and future market returns in 5 commodities, namely, Mustard Seed, Refined Soy Oil, Refined Castor Oil, Crude Sunflower Oil and Raw Yellow Peas. Uni-directional causality from spot to futures market was observed in case of Groundnut, Bajra, Paddy (Basmati) and Maize Feed. Upon going through the research process, it was observed clearly that there is a great scope for improvement, both at policy and implementation levels for the overall development of Commodity Derivative markets in India. Be it the policy makers, traders, farmers or investors, all of them need to participate and work towards a system which is not only robust for them but for the Economy as well.

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Publication Details

Journal
Journal of Informatics Education and Research
Published
2025-03-24
DOI
https://doi.org/10.52783/jier.v5i1.2394
Primary Topic
Grey System Theory Applications
Type
article
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article

Analysing Cause & Effect Lag Relationship between Spot & Future Returns of Agro Commodities

Deepsi
Journal of Informatics Education and Research
Grey System Theory Applications
article

Analysing Cause & Effect Lag Relationship between Spot & Future Returns of Agro Commodities

Deepsi
article en

Abstract

Derivatives market help in reducing volatility in spot markets due to increase in the information flow from future market to the spot market. Also, it attracts the speculators to the spot market and take alternate positions at lower cost. This helps in reducing volatility in spot markets. Derivative markets perform many functions like Price Discovery, reducing volatility spillover, hedging and risk management. The objective of the study was identified to study the causal or lead and lag relationship and analyse Cause & Effect Lag Relationship between Spot & Future Returns of sampled Agro commodities. Ten agricultural commodities frequently traded on NCDEX i.e. Mustard Seed, Refined Soy Oil, Crude Sunflower Oil, Refined Castor Oil, Groundnut, Raw Yellow Peas, Moong, Bajra, Paddy (Basmati) & Maize Feed were considered in the study. Sampled commodities were selected based on March, 2018 observed trading volumes from two major commodity groups of NCDEX, namely Cereals & Spices and Oil & Oil seeds and duration of the study was for 6 years i.e. April 2018 to August 2024. Vector Auto Regression (VAR) Model: VAR model is used to study the causal or lead and lag relationship between spot and future market of the commodities. The Block exogeneity Granger’s causality test along with impulse response function and variance decomposition variance estimates were analyzed. The causality method is applied to the different selected commodities. During the period of study Spot and future prices of all the agro commodities showed fluctuations. Mean spot prices were greater than mean future prices for all agri-commodities except Mustard Seed, Groundnut and Paddy (Basmati) during the period of study. ADF Unit root test showed that time series was not stationary at level 0. However, the time series became stationary at first log transformation for all 10 commodities. There exists high positive significant correlation between the Agri spot and future commodity prices which showed that during the period of study they were moving in the same direction. There exists Bi-directional causality between spot and future market returns in 5 commodities, namely, Mustard Seed, Refined Soy Oil, Refined Castor Oil, Crude Sunflower Oil and Raw Yellow Peas. Uni-directional causality from spot to futures market was observed in case of Groundnut, Bajra, Paddy (Basmati) and Maize Feed. Upon going through the research process, it was observed clearly that there is a great scope for improvement, both at policy and implementation levels for the overall development of Commodity Derivative markets in India. Be it the policy makers, traders, farmers or investors, all of them need to participate and work towards a system which is not only robust for them but for the Economy as well.

Journal of Informatics Education and ResearchVol. 5(1)
Openalex Percentile: Top 94%
Grey System Theory Applications
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