India's Agricultural Commodity Futures Market Ecosystem: An Overview

2017 ◽  
Author(s):  
Velmurugan Palanipappa Shanmugan ◽  
Paul W Armah
Keyword(s):  
Futures Market ◽  
Commodity Futures ◽  
Agricultural Commodity

Cointegration, linear and nonlinear causality

2014 ◽  
Vol 4 (2) ◽  
pp. 157-171 ◽  
Author(s):  
Tarun Kumar Soni
Keyword(s):  
Futures Market ◽  
Commodity Futures ◽  
Futures Contracts ◽  
Spot Price ◽  
Agricultural Commodities ◽  
Agricultural Commodity ◽  
Content Type ◽  
Price Series ◽  
Cointegration Tests ◽  
Linear And Nonlinear

Purpose – The purpose of this paper is to study the market efficiency, unbiasedness and the direction of causality among four agricultural commodity futures contracts for a forecasting horizon of 28 days, 56 days and 84 days which are traded at National Commodity and Derivatives Exchange Ltd. Design/methodology/approach – To analyse the efficiency of futures market in Indian scenario, we focus on maize, chickpea, soybean and wheat which are among the most important agricultural commodities traded in India. In the first step, Augmented Dickey-Fuller test and nonparametric Phillips-Perron approaches have been used to examine the stationarity of all futures and spot price series. After testing the presence of cointegration in futures and spot series using Johansen’s Cointegration approach, the joint restrictions of β 0=0, β 1=1 and β 1=1 on the cointegrating vectors were imposed to test whether the futures price is an unbiased predictor of spot at contract maturity. In the next step, linear Toda and Yamamoto (1995) and the nonparametric Diks and Panchenko (2006) causality tests were applied to examine the direction of causality. Finally, nonlinear test were applied on the vector error correction model (VECM) residuals to investigate whether any remaining causality is strictly nonlinear in nature. Findings – The results of cointegration tests between futures and spot prices of the selected agricultural commodities indicated a long term relationship do exist in three out of four futures contracts. However, the Wald tests results on the cointegrating vectors indicate markets as inefficient and biased. Further, analysis of short-term relationship using alternate tests of causality do not give consistent results for same commodity series indicating that results may vary due to alternate measures and specifications. Finally, if we consider the results of Diks-Panchenko test on the filtered VECM-residuals, results provide evidence that if cointegration is taken into account; neither spot nor future leads or lags the other consistently. Research limitations/implications – The results are based on the sample of four agricultural futures commodity contracts. The study can be extended to a larger sample of contracts and relative efficiency of each contract can be explored. Originality/value – There are very few studies that have explored the efficiency, unbiasedness and direction of causality using both linear and nonlinear techniques for Indian agriculture commodity futures market for different forecasting horizons.

WEATHER SHOCKS AND AGRICULTURAL COMMODITY PRICES IN INDIA

2013 ◽  
Vol 04 (03) ◽  
pp. 1350011
Author(s):  
N. R. BHANUMURTHY ◽  
PAMI DUA ◽  
LOKENDRA KUMAWAT
Keyword(s):  
Structural Change ◽  
Futures Markets ◽  
Commodity Prices ◽  
Futures Market ◽  
Commodity Futures ◽  
Price Formation ◽  
Futures Prices ◽  
Agricultural Commodity ◽  
Spot Prices ◽  
Weather Shocks

We analyze the impact of weather shocks on price formation in spot and futures market for food in India where until the recent introduction of commodity futures markets in 2005, the transmission of these shocks to short-term (spot) price movements was unclear. Hitherto, the price discovery mechanism was weak and end price was expected to be different (mostly higher unless some product prices were administered) from the market-clearing price. In addition, this weak mechanism was expected to result in higher price volatility. The introduction of a futures market is expected to reduce risk, a major component in agricultural production as well as in price formation. Though the commodity futures market in India is nascent, we model transmission of weather shocks to futures and spot prices using monthly data. Based on cointegration analysis, our results suggest strong long-run co-movement between futures prices and spot prices for commodities traded in futures markets. Changes in rainfall affect both futures and spot prices with different lags. However, rainfall shocks generate larger responses from futures prices than from spot prices. Although there could be other factors that affect futures prices, after controlling for fuel prices, our results clearly show the transmission mechanism of weather shocks from futures to spot prices. We also explore the changes in responsiveness of prices of major agricultural commodities to rainfall with introduction of futures contracts to facilitate the pass-through of various types of shocks to agricultural commodity prices. Using smooth transition regression, we find that the bivariate relationships between rainfall and prices of rice, wheat and pulses show some nonlinearity with the structural change happening after the introduction of futures market. These relations are found to be much stronger in the post-structural change period that broadly coincides with the introduction of futures market.

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

2021 ◽  
pp. 105377
Author(s):  
Adam Makkonen ◽  
Daniel Vallström ◽  
Gazi Salah Uddin ◽  
Md Lutfur Rahman ◽  
Michel Ferreira Cardia Haddad
Keyword(s):  
Temperature Anomaly ◽  
Commodity Futures ◽  
Effect Of Temperature ◽  
Agricultural Commodity ◽  
Macroeconomic Fundamentals
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