Spot and future price relationship of black gram and green gram

Introduction

Black gram and green gram are important pulse crops in India and contribute significantly to agricultural production, trade, nutritional security and farm income in Maharashtra. India is the largest producer and consumer of pulses. Among pulses, black gram and green gram are major kharif pulses grown in Marathwada and Vidarbha regions. Maharashtra is one of the leading pulse producing states, and Latur is known as the pulse bowl of Maharashtra. These crops also improve soil fertility through nitrogen fixation and fit well in rainfed cropping systems. The prices of agricultural commodities fluctuate over time due to seasonality, weather, demandsupply mismatch, market arrivals, storage, transportation, government policies and market expectations. In case of pulses, price volatility is higher due to gap between demand and supply and high import dependence. This price instability creates risk for farmers, traders, processors and consumers. Farmers face uncertainty about prices they will receive, which affects their sowing and selling decisions and often leads to distress sale. To manage price risk, futures markets have been established. Futures market is an organized exchange where standardized contracts for future delivery are traded. In India, National Commodity and Derivatives Exchange (NCDEX) provides futures trading for agricultural commodities. Futures markets perform two important functions price discovery and price risk management through hedging. Futures prices reflect collective expectations of market participants about future demand, supply and provide advance signals for spot market movements. If futures market is efficient, spot and future prices should be closely related and integrated. Understanding spot-future relationship is important for farmers to decide when to sell, for traders and dal mill owners to hedge risk, and for policymakers to frame price policies. Similarly, information on seasonal and cyclical variations helps in planning timing of sale, storage and marketing. Although studies exist for cereals and oilseeds, limited work with long period data is available for black gram and green gram in Maharashtra. Therefore, the present study was undertaken to examine spot and future price relationship and seasonal and cyclical variations in selected markets of Maharashtra during 2005-2025. Objectives 1. To examine the relationship between spot and future prices of black gram and green gram. 2. To study the seasonal and cyclical variations in prices of black gram and green gram.

Methodology 1. Selection of Crop

For the study, two crops i.e. black gram and green gram were selected.

Selection of Major Market

The study has been confined to the Maharashtra state. For black gram, Latur and Amravati APMCs were chosen as they are major trading and arrivals centres in Maharashtra. For green gram, Akola and Washim APMCs were selected due to their high trade volume and importance in price discovery.

Period of Study

The present study was based on time series monthly data of prices. The data prices of black gram and green gram from the selected APMCs were collected for a period of last 20 years from 2005-2025.

Sources of Data

The study was based on secondary data. Spot prices were collected from the official website of the Directorate of Marketing and Inspection, Government of India www.agmarknet.gov.in. The future prices were collected from India's leading agricultural commodity exchange i.e. NCDEX (National Commodity and Derivatives Exchange), the official website of the NCDEX is https://www.ncdex.com. The online portal CEDA (Centre for Economic Data and Analysis) https;//agmarket.ceda.ashoka.edu.in/ was also referred for data verification.

Method of Analysis

The collected data were analyzed using EViews 12 statistical software and the results were presented in the tables in order to bring out generalization of facts from which meaningful inference could be drawn.

Analytical Tools

The collected data was analyzed using suitable analytical tools as described below.

A. Relationship between spot and future prices of black gram green 1) Correlation coefficient

To study the relationship between spot and future prices, the method of correlation was used. The correlation is the measure of degree of relationship amongts two series i.e. spot and future. The formula used for calculating the coefficient of correlation is as follow:

Where, r = correlation coefficient x, y = two related variable n = sample size 2) Regression analysis Regression analysis was carried out to a certain the relationship between spot prices and one month lagged future prices. The simple linear regression model was used for analysis. The equation fitted for the purpose was specified as follows:

Where Y = Spot prices a = intercept b = regression coefficient X = one month lagged future prices

B) Seasonal and Cyclical variations in prices of black gram and green gram 1) Estimation of seasonal Indices of monthly data

Most widely used method of measuring seasonal fluctuations i.e method of moving average was used to calculate seasonal indices. To measure the seasonal variations in spot and future prices, seasonal indices were calculating by employing twelve months ratio to moving average method.

2) Cyclical Indices

The residual method of estimating cyclical movement in time series was used for estimating cyclical indices, after eliminating the seasonal variation and trend components.

Results and Discussion

The data collected were analyzed in relation to each of the specific objectives of the study and results have been tabulated. In this chapter, results of the analysis are presented and discussed in the following section.

 Correlation and Regression analysis  Seasonal and Cyclical variations in spot and future prices 1 Correlation Regression analysis 1.1 Descriptive statistics

Descriptive Statistics were worked out to study the behaviour and distribution of spot and future prices of black gram and green gram during the study period. The descriptive statistics of Latur, Amravati spot prices and future prices of black gram are presented in Table 1 and The descriptive statistics of Akola, Washim spot prices and future prices of green gram are presented in Table 2.

Simple Correlation coefficient

The simple correlation analysis was carried out to examine the degree of association between spot prices and one month lag future prices of black gram and green gram. The simple correlation coefficient between spot and lag future prices of black gram and green gram are presented in Table 3 and Table 4. It is observed from Table 3 that, the correlation coefficient between Latur spot prices and lag future prices was 0.89, whereas between Amravati spot prices and lag future prices was 0.59. The correlation coefficient between Latur and Amravati spot prices was 0.65 and all correlations were significant at 5 per cent level. The results indicated a moderate to high positive correlation between spot and lag future prices in both markets. This implies that an increase in future prices is associated with an increase in spot prices, indicating a close relationship between spot and future markets during the study period. It is observed from the table 4 that, the strong positive correlation coefficient between Akola spot and lag future prices was 0.93 and 0.91 between Washim spot and lag future prices. Correlation coefficient between Akola and Washim spot prices was 0.92, all significant at 5% level. This indicates close integration between spot and future markets of green gram during the study period.

Linear regression analysis

Linear regression analysis was carried out to examine the effect of one month lag future prices on spot prices of black gram and green gram. The estimated regression coefficients are presented in Table 5 and Table 6. It is observed from the Table 5 the regression coefficient of one-month lag future price was 0.82 for Latur and 0.54 for Amravati, both positive and significant at 10% level. Intercepts were 526.76 and 1586.95 respectively. This indicates that lag future prices have significant positive influence on spot prices, where 10% increase in future price raises spot price by 0.82% in Latur and 0.54% in Amravati. It is observed from Table 6 the regression coefficient of onemonth lag future price was 0.79 for Akola and 0.76 for Washim, both positive and significant at 5% level. Intercepts were 726.63 and 743.59 respectively. This shows lag future prices have significant positive influence on green gram spot prices, with Akola responding more strongly to future price changes than Washim.

Seasonal and Cyclical variations in spot and future prices Seasonal Variations

The seasonal indices of spot and future prices of black gram and green gram were worked out to study the seasonal variations in prices during different months of the year. The seasonal indices for black gram and green gram are presented in Table 7 and Table 8. It observed from Table 7 that in Latur market, the highest seasonal index was recorded during November (109.32), followed by September (107.08), followed by October (105.90) and December (104.62) while the lowest seasonal index was observed during July (89.01). In Amravati market, the highest seasonal index was recorded during September (108.25), followed by November (103.30), followed by October (102.39) and December (101.72), whereas the lowest seasonal index was observed during January (94.86). similarly, the highest seasonal index was observed in future markets the month of August (103.80), followed by May (103.03), followed by April (101.99), followed by November (101.28), followed by June (101.27), followed by July (101.04) and September (100.88), Whereas the lowest in February (94.72). The result indicated that seasonal variations existed in both spot and future prices of black gram during the study period.

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