Asymmetric price adjustment and price discovery in spot and futures markets of agricultural commodities

Author(s):  
Zhuo Chen ◽  
Bo Yan ◽  
Hanwen Kang ◽  
Liyu Liu
2020 ◽  
Vol 23 (1) ◽  
pp. 53-69
Author(s):  
Keshab Shrestha ◽  
Ravichandran Subramaniam ◽  
Thangarajah Thiyagarajan

In this study, we empirically analyze the contribution of futures markets to the price discovery process for seven agricultural commodities using the generalized information share proposed by Lien and Shrestha (2014) and component share based on the permanent-temporary decomposition proposed by Gonzalo and Granger (1995). We find that most of the price discovery takes place in the futures markets with the exception of cocoa. Our results show that futures markets play an important role in price discovery process. These results are important to academicians, practitioners, policymakers as well as business leaders.


2021 ◽  
pp. 227797522098574
Author(s):  
Bhabani Sankar Rout ◽  
Nupur Moni Das ◽  
K. Chandrasekhara Rao

The present work has been designed to intensely investigate the capability of the commodity futures market in achieving the aim of price discovery. Further, the downside of the cash and futures market and transfer of the risk to other markets has also been studied using VaR, and Bivariate EGARCH. The findings of the work point that the metal commodity derivative market helps in the efficient discovery of price in the spot market except for nickel. But, in the case of the agricultural commodities, the spot is found to be leading and thus there is no price discovery except turmeric. On the other hand, the volatility spillover is bidirectional for both agri and metal commodities except copper, where volatility spills only from futures to spot. Further, the effect of negative shock informational bias differs from commodity to commodity, irrespective of metal or agriculture.


Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 115
Author(s):  
Osama Ahmed

This paper examines the world wheat market leadership using price discovery occurring in wheat futures markets of the United States (U.S.) and Europe. An error correction model (ECM) generalized autoregressive conditional heteroskedasticity (GARCH), and semi-parametric dynamic copula methods are used for this purpose. The results indicate a positive link between U.S. and Europe price discovery which is stronger, fluctuating less after August 2010 because of a drought occurring in the Black Sea region, and then lessens, fluctuating more after 2015 with the changing wheat trade map. Furthermore, after 2015, wheat market leadership moved from the U.S. to the European market, meaning price discovery is primarily located by the Marché à Terme International de France (MATIF) futures market.


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