In 2008, wheat futures prices spiked and then crashed along with prices for other agricultural and nonagricultural commodities. Market observers offered several theories to explain this common movement, or comovement, in prices, and have proposed policies to address the perceived problem of excessive price volatility. The design of an appropriate policy response would benefit from a better understanding of the cause of the observed price movements. This study uses an econometric model to decompose observed wheat prices into a set of economic factors and measure the relative contribution of each factor to observed price changes. Findings show that market-specific shocks related to supply and demand for wheat were the dominant cause of price spikes in the three U.S. wheat futures markets. Fluctuations in the global macroeconomy associated with broadbased demand shocks were relatively less significant for wheat than for other commodities like crude oil and corn. Little evidence suggests commodity index trading contributed to recent price spikes. Tables and figures. This is a print on demand report.

In 2008, wheat futures prices spiked and then crashed along with prices for other agri-cultural and nonagricultural commodities. Market observers offered several theories to explain this common movement, or comovement, in prices, and have proposed policies to address the perceived problem of excessive price volatility. The design of an appropriate policy response would benefit from a better understanding of the cause of the observed price movements. This study uses an econometric model to decompose observed wheat prices into a set of economic factors and measure the relative contribution of each factor to observed price changes. Findings show that market-specific shocks related to supply and demand for wheat were the dominant cause of price spikes in the three U.S. wheat futures markets. Fluctuations in the global macroeconomy associated with broadbased demand shocks were relatively less significant for wheat than for other commodities like crude oil and corn. Finally, little evidence suggests commodity index trading contributed to recent price spikes.

In 2008, wheat futures prices spiked and then crashed along with prices for other agricultural and nonagricultural commodities. Market observers offered several theories to explain this common movement, or comovement, in prices, and have proposed policies to address the perceived problem of excessive price volatility. The design of an appropriate policy response would benefit from a better understanding of the cause of the observed price movements. This study uses an econometric model to decompose observed wheat prices into a set of economic factors and measure the relative contribution of each factor to observed price changes. Findings show that market-specific shocks related to supply and demand for wheat were the dominant cause of price spikes in the three U.S. wheat futures markets. Fluctuations in the global macroeconomy associated with broadbased demand shocks were relatively less significant for wheat than for other commodities like crude oil and corn. Finally, little evidence suggests commodity index trading contributed to recent price spikes.

The six volumes LNCS 11619-11624 constitute the refereed proceedings of the 19th International Conference on Computational Science and Its Applications, ICCSA 2019, held in Saint Petersburg, Russia, in July 2019. The 64 full papers, 10 short papers and 259 workshop papers presented were carefully reviewed and selected form numerous submissions. The 64 full papers are organized in the following five general tracks: computational methods, algorithms and scientific applications; high performance computing and networks; geometric modeling, graphics and visualization; advanced and emerging applications; and information systems and technologies. The 259 workshop papers were presented at 33 workshops in various areas of computational sciences, ranging from computational science technologies to specific areas of computational sciences, such as software engineering, security, artificial intelligence and blockchain technologies.