Opening Cross: There’s a Storm Coming, Mr. Wayne, Part II

Storms are predators, sucking energy from weather fronts around them, gaining strength and momentum, wreaking havoc on homes, humanity and the commodities markets. Now, Hurricane Isaac batters New Orleans, leaving more than a million people without power; corn and soy wither under drought conditions in the Midwest; climate change promises more unpredictable weather forces; and an economic storm is set to re-ignite as Occupy Wall Street plans an anniversary protest for Sept. 17. But what if the impact of these forces of nature could be better predicted and—if not tamed—better understood?
In recent issues of Inside Market Data, we’ve seen a distinct trend of increased demand for energy and commodities data—much of it coming from those directly involved in energy generation and supply seeking to understand the impact of demand and production on the prices they pay and can charge, but also among trading firms seeking a better understanding of these commodities through more granular data, for their own trading activities and for portfolios of client funds invested in non-traditional asset classes.
One issue is that the commodities markets don’t move with the same speed traders have become accustomed to in other markets, so the same levels of data are not available. For example, Dow Jones’ German newswire is increasing the frequency of commodities data to provide its clients, by adding intraday downloads from interdealer broker GFI, to provide more timely updates on price movements.
However, something that is fast-moving—and which can have a major and sudden impact on commodities production and prices—is weather. Heatwaves drive up air conditioning use and demand for electricity, while freak snowstorms drive demand for heating oil. Too much or too little rain can wipe out crops, while storms and natural disasters can leave millions without power, close oil rigs and power plants and disrupt shipping, driving up both demand and the cost of supply.
To address this need for data on how commodities and their related infrastructures of production and supply are at risk of—and affected by—natural disasters and weather phenomena, Thomson Reuters has launched an Interactive Map in its Eikon desktop that allows users to track every part of the supply and production chain, and assess how these would be affected by freak events.
As money flows shift into commodities from commoditized assets, the markets are trying to apply the same levels of technical and predictive analytics that are readily available in the most liquid and accessible asset classes, and to incorporate as much contextual supporting data as possible, and address these to new marketplaces. Imagine, for example, being able to apply tools such as EquityFeed’s Filter Builder—to which the vendor is adding a raft of new technical indicators to meet the demands of increasingly sophisticated active traders—to commodities markets; or applying the predictive decision support analytics of Lucena Research’s new QuantDesk platform to optimize a portfolio of different commodities. Equally, additional content from ESG (environmental, social and governance) data providers such as GMI could become even more relevant for analyzing commodities, while analysis of social media and sentiment will provide granular information about the ultimate end-users of commodities—i.e. consumers—that could also impact prices.
And speaking of social data (or, at least, social diseases), MTV announced last week that its wind-filled and tempestuous alternative reality show Jersey Shore will end after the upcoming season, bringing calmer weather to Seaside Heights, NJ (and economic hardship to gyms, tanning salons and laundromats in the area). So farewell Snooki, Situation, Jwoww et al. We’ll miss you, in the same way that we miss hurricanes. But unlike the unpredictable cast of Jersey Shore, at least in future we will be able to better understand the forces behind storms and better predict their impact on everything, from the local populace to market prices.
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