Price Discovery on the International Soybean Futures Markets: A Threshold Co‐Integration Approach

Abstract

This paper investigates the lead-lag relationships among soybean prices in United States, Brazilian, and Chinese futures markets. We focus on both long-run price co-movements and on short-run price relationships. Various co-integration methodologies and causality tests are applied to examine the changes in price relationships over time. The empirical results indicate the following: (a) the soybean futures market in the U.S. is still the most important and influential market, and the U.S. price, in the long-term, leads price changes in Brazil and China; (b) in the short-term, the overnight return of U.S. soybean futures and the daytime return of Chinese No. 1 soybean futures contemporaneously affect each other, but there is no significant causality between U.S. overnight return and the daytime return of Chinese No. 2 soybean futures; and, (c) a weak temporal seasonal causality between U.S. and Brazilian soybean futures price exists and more often than not Brazilian futures lead U.S. futures during the Brazilian growing season.

Return and volatility transmission between China's and international crude oil futures markets: A first look

“…An equally noteworthy factor is mentioned in Protopapadakis and Stoll's study (1983) in which they point out that an international price relationship for an identical commodity traded across different countries should generally follow the law of one price for a commodity, and such an relationship may be investigated in “its purest form” when commodity futures prices are used. As Chinese commodity futures markets as a whole have become the most actively traded since 2010 (with their exchanges having the highest commodity futures trading volume in the world), there is a growing amount of literature on the linkages of Chinese commodity futures with other global major commodities futures markets: Fung, Leung, and Xu (2003); Fung, Liu, and Tse (2010); Fung, Tse, Yau, and Zhao (2013) examining the information transmission between various Chinese nonoil commodity futures contracts and the corresponding global futures markets, Jiang, Su, Todorova, and Roca (2016) examining the spillovers between the United States and Chinese agricultural futures, and Li and Hayes (2017) investigating price discovery on the Chinese, United States, and Brazilian soybean futures markets.…”

Market Integration in the International Market of Soybeans: Are GM Soy and Non-GM Soy Markets Integrated?

“…They show a 1% increase in the American FOB price will cause a 0.33% increase in Brazilian price and a lower 0.25% increase for Argentinian prices within one month. This reflects the traditional role as price maker that USA has had on the international soybeans market, with the CBOT prices acting as the reference prices for the market, as already identified by several studies (Machado & Margarido, 2004;Margarido, Turolla, & Bueno, 2004;Li & Hayes, 2016).…”

“…They found bidirectional effects, lead by CBOT who has the greater impact. Li and Hayes (2016) studied future prices in China, USA, and Brazil, from 2005 to 2015, using non-linear cointegration and weak exogeneity, as well as sample splitting. They found instead that CBOT prices retain single leadership over the futures prices market, although there is a weakening trend in the link, and in addition it is affected by seasonal variations with Brazil adopting temporal leadership during its marketing season.…”

Research on Futures Price Volatility Transmission Effect: Evidence from the CBOT and DCE Soybean Futures

“…DCE and CBOT Soy product futures price data were derived from the respective statistical database of the From the model estimation results, we get the duration and value of the probability of high volatility in the duration and value of probability. Market volatility in the high volatility phase sequence is significantly higher than the low volatility, and the mean is greater than the mean of the low volatility phase [7][8]. Comparing similarities and differences between DCE and CBOT volatility, it gives the trajectory of the value of smoothed probabilities, in each state within the range of samples of the various markets.…”