World Soybean Prices, 1998-Present

*For September 5, 2003, original data taken from the FAO showed a weekly price of 2.36 US$/ton; this data was corrected to reflect a price of 236 US$/ton.

World Soybean Returns, 2001-Present

The graph below shows the cases in which the value of the realized returns (log returns of future prices contracts expiring between 1 and 3 months) are higher than the forecast the 95% conditional quantile for the log return on the following day based on a model that includes daily returns since 2001. When the blue line (realized return) is over the red line (forecasted 95th percentile returns) it means that the realize return is an abnormality and we expect it to fall under the 95th percentile return in the following day.

The daily global news continues to be inundated with stories of rising food prices, and accompanying rises in poverty and hunger. Recent droughts in China have been added to the list of factors driving food prices, specifically commodity prices, up around the world. Policymakers are now faced with decisions regarding the appropriate response to these increases.

While rises in the price of staple commodities such as wheat and maize do pose major food security challenges, one of the major factors threatening global food security remains extreme price fluctuations and the observed political and market overreaction that normally follows. In 2007-08, volatile prices led many major food producers to impose knee-jerk reactions such as export restrictions. As was seen during this previous crisis, a halt, or even a restriction, in exports from large exporting countries will put more pressure on commodity prices, dramatically affecting consumers worldwide. Such an impact is magnified for poor consumers, who spend a large portion of their incomes on food.

The graph above uses the estimator described in Martins-Filho, Torero and Yao (2010) to estimate conditional quantiles for log returns of future prices (contracts expiring between one and three months) of hard wheat, soft wheat, corn and soybeans. This model draws on extensive research into returns on agricultural commodity prices to explain when such price fluctuations and jumps are abnormally high given past observations on prices. This deeper understanding may help prevent knee-jerk policy reactions by discouraging market overreaction and encouraging market stability.

Watch Senior IFPRI Researcher and University of Colorado Professor Carlos Martins-Filho discuss the research behind these powerful tools.

Martins-FilhoToreroYao2010.pdf180.68 KB
Filho_Torero_G20_Presentation.pdf887.41 KB