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.

Price discovery and volatility spillover: an empirical evidence from spot and futures agricultural commodity markets in India

2020 ◽  
Vol 10 (4) ◽  
pp. 447-473 ◽  
Author(s):  
Manogna R L ◽  
Aswini Kumar Mishra
Keyword(s):  
Granger Causality ◽  
Futures Markets ◽  
Price Discovery ◽  
Spillover Effects ◽  
Futures Market ◽  
Commodity Markets ◽  
Volatility Spillover ◽  
Agricultural Commodity ◽  
Content Type ◽  
Spot Prices

PurposePrice discovery and spillover effect are prominent indicators in the commodity futures market to protect the interest of consumers, farmers and to hedge sharp price fluctuations. The purpose of this paper is to investigate empirically the price discovery and volatility spillover in Indian agriculture spot and futures commodity markets.Design/methodology/approachThis study uses Granger causality, vector error correction model (VECM) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) to examines the price discovery and spillover effects for nine most liquid agricultural commodities in spot and futures markets traded on National Commodity and Derivatives Exchange (NCDEX).FindingsThe VECM results show that price discovery exists in all the nine commodities with futures market leading the spot in case of six commodities, namely soybean seed, coriander, turmeric, castor seed, guar seed and chana. Whereas in case of three commodities (cotton seed, rape mustard seed and jeera), price discovery takes place in the spot market. The Granger causality tests indicate that futures markets have stronger ability to predict spot prices. Supporting these, the results from EGARCH volatility test reveal that there exist mutual spillover effects on futures and spot markets. Thus, it could be inferred that futures market is more efficient in price discovery of agricultural commodities in India.Research limitations/implicationsThese results can help the market participants to benefit by hedging out the uncertainty and the policymakers to design futures contracts to improve the efficiency of the agricultural commodity derivatives market.Practical implicationsThe findings provide fresh view on lead–lag relationship between future and spot prices using the latest data confirming that futures market indeed is dominant in price discovery.Originality/valueThere are very few studies that have explored the efficiency of the agricultural commodity spot and futures markets in India using both price discovery and volatility spillover in a detailed manner, especially at the individual agriculture commodity level.

scholarly journals A Study of the Economic Functions of the Maine Potato Futures Market

1980 ◽  
Vol 9 (1) ◽  
pp. 51-61
Author(s):  
Jeff Sooy ◽  
Ben Branch
Keyword(s):  
Futures Markets ◽  
Futures Market ◽  
Extensive Study ◽  
Convincing Evidence ◽  
Recent Time ◽  
The Other ◽  
Futures Prices ◽  
Spot Prices ◽  
Time Period ◽  
Maine Potato

In an update and extension of prior work this study found that the potato futures markets continued to provide very unreliable forecasts of subsequent spot prices. On the other hand and contrary to some past studies an extensive study here failed to turn up any convincing evidence of a cobweb pricing relationship. Moreover the increasing volatility of potato futures prices in the more recent time period raises questions regarding their value as hedging vehicles. Finally it is argued that the market's efficiency might be improved by expanding the current Maine potato contract to permit delivery of round white potatoes grown outside Maine.

Relationship between Coffee Prices in Spot and Futures Markets-An Empirical Analysis

2020 ◽  
pp. 180-188
Keyword(s):  
New York ◽  
Correlation Coefficients ◽  
Strong Relationship ◽  
Futures Market ◽  
Regression Coefficients ◽  
Futures Prices ◽  
Market Prices ◽  
Spot Prices ◽  
Correlation And Regression Analysis ◽  
Highly Correlated

The present study explored the relationship between spot and futures coffee prices. The Correlation and Regression analysis were carried out based on monthly observations of International Coffee Organization (ICO) indicator prices of the four groups (Colombian Milds, Other Milds, Brazilian Naturals, and Robustas) representing Spot markets and the averages of 2nd and 3rd positions of the Intercontinental Exchange (ICE) New York for Arabica and ICE Europe for Robusta representing the Futures market for the period 1990 to 2019. The study also used the monthly average prices paid to coffee growers in India from 1990 to 2019. The estimated correlation coefficients indicated both the Futures prices and Spot prices of coffee are highly correlated. Further, estimated regression coefficients revealed a very strong relationship between Futures prices and Spot prices for all four ICO group indicator prices. Hence, the ICE New York (Arabica) and ICE Europe (Robusta) coffee futures prices are very closely related to Spot prices. The estimated regression coefficients between Futures prices and the price paid to coffee growers in India confirmed the positive relationship, but the dispersion of more prices over the trend line indicates a lesser degree of correlation between the price paid to growers at India and Futures market prices during the study period.

Pricing of Futures Contracts

2018 ◽  
Author(s):  
Timothy A. Krause
Keyword(s):  
Fair Value ◽  
Commodity Futures ◽  
Futures Contracts ◽  
Spot Price ◽  
Futures Prices ◽  
No Arbitrage ◽  
Spot Prices ◽  
Cost Of Carry ◽  
Contract Expiration ◽  
The Cost

This chapter examines the relation between futures prices relative to the spot price of the underlying asset. Basic futures pricing is characterized by the convergence of futures and spot prices during the delivery period just before contract expiration. However, “no arbitrage” arguments that dictate the fair value of futures contracts largely determine pricing relations before expiration. Although the cost of carry model in its various forms largely determines futures prices before expiration, the chapter presents alternative explanations. Related commodity futures complexes exhibit mean-reverting behavior, as seen in commodity spread markets and other interrelated commodities. Energy commodity futures prices can be somewhat accurately modeled as a generalized autoregressive conditional heteroskedastic (GARCH) process, although whether these models provide economically significant excess returns is uncertain.

Financialization of Commodity Markets

2018 ◽  
Author(s):  
Kyle J. Putnam
Keyword(s):  
Business Cycle ◽  
Futures Markets ◽  
Commodity Price ◽  
Commodity Markets ◽  
Commodity Futures ◽  
Futures Prices ◽  
Price Behavior ◽  
Risk And Return ◽  
Commodity Futures Markets ◽  
Asset Class

In the early 2000s, financial investors began pouring billions of dollars into the commodity futures markets seeking the unique investment benefits of this distinct asset class. This “financialization” process has called into question the fundamental risk and return properties of commodity futures as evidence has emerged favoring the idea that the massive increase in investor flows caused a rise in futures prices, volatility, and intra- and intermarket return correlations. However, a contrarian line of research contends that the effects of the new “speculative” capital on the futures markets are unsubstantiated and the increased participation of financial investors poses little consequence to the economics of the marketplace. This latter line of literature maintains that the investment benefits of commodity futures have not been diminished and that fundamental factors and business cycle variations can explain the observed changes in commodity price behavior.

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