Unbiased Estimation, Price Discovery, and Market Efficiency: Futures Prices and Spot Prices

2008 ◽  
Vol 28 (8) ◽  
pp. 2-11 ◽  
Author(s):  
Rong CHEN ◽  
Zhen-long ZHENG
Keyword(s):  
Market Efficiency ◽  
Price Discovery ◽  
Unbiased Estimation ◽  
Futures Prices ◽  
Spot Prices

Market efficiency and price risk management of agricultural commodity prices in India

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Manogna R.L. ◽  
Aswini Kumar Mishra
Keyword(s):  
Risk Management ◽  
Market Efficiency ◽  
Price Discovery ◽  
The Other ◽  
Price Risk ◽  
Futures Prices ◽  
Agricultural Commodities ◽  
Content Type ◽  
Price Risk Management ◽  
Guar Seed

Purpose Market efficiency leads to transparent and fair price discovery of commodity markets, thus enhancing the value chain for competitive benefit. The purpose of this paper is to investigate the market efficiency of Indian agricultural commodities at spot, futures and mandi markets apart from exploring price risk management in these markets. Design/methodology/approach This study uses Johansen co-integration, vector error correction model and granger causality for analyzing market efficiency of the nine most liquid agricultural commodities across three markets, namely, spot, futures and mandi. All these nine commodities are traded on National Commodity and Derivatives Exchange. Findings The statistical results indicate price discovery exists in the mandi market and spot market leading to futures prices. Mandi price returns are seen to negatively influence futures returns in the case of cotton seed, guar seed and spot returns in the case of jeera, coriander and chana. For castor seed, the three markets are seen to have no long run relationship. The results of Granger causality reveal short run relationship between all the three markets in the case of soybean seed and coriander. In these commodities, prices in all three markets are capable of predicting the prices in the other markets. For the case of cottonseed, Rape Mustard seed, jeera, guar seed, the results indicate unidirectional causality between the mandi markets and the other two markets. Research limitations/implications These results shall facilitate policymakers to explore intervention through integrated agri-platform (IAP) in price discovery and market efficiency. Practical implications The results of this study are useful in understanding the price discovery of mandi markets and its role in the spot and futures market. Agricultural commodities price discovery depends upon the integration of all these three markets. Introduction of IAP as described in the paper shall facilitate price risk management apart from improving the efficiency of price discovery. Originality/value To the best of the knowledge, this is the first study considering mandi, spot and futures prices in the price discovery process in India. In addition, this study found the role of mandi markets in serving the economic function of price discovery and price risk management. Hence, suggests for policy intervention for Indian agricultural commodities to manage price risk.

An Empirical Analysis of Market Efficiency and Price Discovery in Indian Commodity Market

2018 ◽  
Vol 19 (3) ◽  
pp. 771-789 ◽  
Author(s):  
Shashi Gupta ◽  
Himanshu Choudhary ◽  
D. R. Agarwal
Keyword(s):  
Error Correction ◽  
Market Efficiency ◽  
Price Discovery ◽  
Correction Term ◽  
Futures Market ◽  
Commodity Futures ◽  
Spot Price ◽  
Futures Prices ◽  
Short Term ◽  
Important Indicator

The present article is an attempt to empirically investigate the long-term market efficiency and price discovery in Indian commodity futures market. The study has been conducted with eight commodities which include two agricultural commodities, two industrial commodities, two precious metal and two energy commodities. Sophisticated statistical methods like restricted cointegration and vector error correction model (VECM) are used to analyse the spot and futures prices time series. Restricted cointegration test shows that near-month futures prices for all the commodities are cointegrated with the spot prices but futures prices of all the commodities are inefficient to predict the future spot price. Indian commodity futures market evidenced as the thinly traded market (Kumar & Pandey, 2013, Journal of Indian Business Research, 5(2), 101–121) rejects the null hypothesis of efficiency and unbiasedness for all the eight commodities which reconfirms the result of Fortenbery and Zapata (1997, Journal of Futures Markets, 17(3), 279–301). The presence of short-term biases in the Indian futures market is evidenced in the results of VECM model which indicates the presence of informational efficiency. The statistically significant value of past prices of spot and futures confirm the short-term inefficiency and biasedness. The significant value of error correction term (ECT) of futures prices suggests that commodity futures are the most important indicator of commodity price movements. The important implication of the results is for market traders. They can use the futures prices to discover the new equilibrium and earn profits by transmitting it to the spot market. The better understanding of the interconnectedness of these market would be useful for policymakers who try to establish stability in the financial markets.

scholarly journals Price Discovery Mechanism in Spot and Futures Market of Agricultural Commodities: The Case of India

2018 ◽  
Vol 5 (2) ◽  
Author(s):  
Minakshi .
Keyword(s):  
Price Discovery ◽  
Emerging Market ◽  
Futures Prices ◽  
Correction Model ◽  
Vector Error Correction ◽  
Spot Prices ◽  
Vector Error ◽  
Long Run ◽  
The Relationship

There has been increasing focus by emerging market researchers, policymakers and regulators for investigating price discovery, relationship between future and physical market and accessible trading and risk management instruments for the benefit of various stakeholders and thus contributing to the development of literature. The central question of this paper is examining the role of influence of one market on the other and the role of each market segment in price discovery in the Indian context. Johansen Vector Error Correction Model (VECM) has been employed to examine the relationship between the spot and futures prices. The cointegration results do not confirm the existence of long-run relationship between spot and futures prices. It is thus, implied that futures prices unlikely serve as market expectations of subsequent spot prices of selected agri-commodities in India and do not help in price discovery process.

scholarly journals THE IMPACT OF PRICE VARIABILITY ON CASH/FUTURES MARKET RELATIONSHIPS: IMPLICATIONS FOR MARKET EFFICIENCY AND PRICE DISCOVERY

2015 ◽  
Vol 47 (4) ◽  
pp. 539-559 ◽  
Author(s):  
CARLOS ARNADE ◽  
LINWOOD HOFFMAN
Keyword(s):  
Market Efficiency ◽  
Price Discovery ◽  
Discovery Process ◽  
Futures Prices ◽  
Price Variability ◽  
Long Run ◽  
Equilibrium Relationship ◽  
Short Run ◽  
The Impact ◽  
Price Discovery Process

AbstractThis study investigates the relationship between cash and futures prices of soybeans and soybean meal from 1992 to 2013. Error correction models are estimated for the prices of both commodities. An exogenous measure of price variability is included in both models to determine if variability increases the speed with which cash and futures prices return to their long-run equilibrium relationship. This is used to measure the impact of price variability on short-run market efficiency and the price discovery process. The findings indicate that the level of price variability influences market adjustment rates and the price discovery process.

A tale of two coffees? Analysing interaction and futures market efficiency

2020 ◽  
Vol 37 (1) ◽  
pp. 89-109
Author(s):  
Mark J. Holmes ◽  
Jesús Otero
Keyword(s):  
Market Efficiency ◽  
Unit Root ◽  
Futures Market ◽  
Recursive Estimation ◽  
Futures Contracts ◽  
Futures Prices ◽  
Content Type ◽  
Spot Prices ◽  
Unit Root Testing ◽  
Price Differentials

Purpose The purpose of this paper is to assess the informational efficiency of Arabica (other milds) and Robusta coffee futures markets in terms of predicting future coffee spot prices. Design/methodology/approach Futures market efficiency is associated with the existence of a long-run equilibrium relationship between spot and future prices such that coffee futures prices are unbiased predictors of future spot prices. This study applies unit root testing to daily data for futures-spot price differentials. A range of maturities for futures contracts are considered, and the study also uses a recursive approach to consider time variation in futures market efficiency. Findings The other milds and Robusta futures prices tend to be unbiased predictors for their own respective spot prices. The paper further finds that other milds and Robusta futures prices are unbiased predictors of the respective Robusta and other milds spot prices. Recursive estimation suggests that the futures market efficiency associated with these cross cases has increased, though with no clear link to the implementation of the 2007 International Coffee Agreement. Originality/value The paper draws new insights into futures market efficiency by examining the two key types of coffee and analyses the potential interactions between them. Hitherto, no attention has been paid to futures contracts of the Robusta variety. The employment of unit root testing of spot futures coffee price differentials can be viewed as more stringent than an approach based on non-cointegration testing.

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.

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