A Glimpse Behind the Commodity Trading Curtain

Yesterday’s FT carried an interesting article about a Glencore trade in wheat and corn.  FT is a royal PITA to quote from, so I’ll just recapitulate.  In brief, as the Russian drought was beginning, Glencore received early reports from “Russian farm assets” of rapidly deteriorating growing conditions in Russia.  It bought wheat and corn, and profited handsomely from the trade.  It claims that such proprietary trades are exceptional for the firm.

More controversially, on 3 August, 2010 Yury Oganev, Glencore’s Russian grain division chief, publicly advocated a ban on Russian exports (a position not endorsed by Glencore).  Two days later Russia indeed banned exports.  Glencore claims that its export business wasn’t helped by the ban, but note the dog that isn’t barking:  the company does not make any statements about whether profits from the wheat and corn trade more than offset the loss to the export business.

Several things bear noting here.

First, this is a classic example of how information is generated and used in commodity markets.  Market participants with physical assets collect information on supply and demand fundamentals, and use that information in their trading.  It is trading on private information, and it tends to contribute to price discovery–as well as generate profits for those with the information advantage.  Such private information tends to reduce market liquidity and impose costs on the (relatively) uninformed, but that’s part of the inherent trade-off between price informativeness and liquidity.

Second, this shows why trading firms with physical assets can have advantages.  Ownership of these assets helps produce valuable information on fundamentals.

Third, this is “speculation,” but it illustrates how such speculation can actually improve the allocation of resources.  Glencore had an early warning of an impending shortage.  It traded on that information, thereby causing prices to reflect it.  This provided a signal that other market participants could use  to take actions to mitigate the effects of the drought.  In particular, market participants who base their consumption and storage decisions on market prices would tend to adjust those decisions in response to the price changes.  The magnitude, or value, of those adjustments is impossible to quantify, but are conceivably large.  In particular, delayed reaction to the drought information would likely have resulted in greater consumption prior to the information becoming public, which in turn would have led to a bigger price spike when it became widely known.

Fourth, the actions of Oganev are far less admirable, in particular if he made the public call for an export ban after the trade was put on.  I believe that the Russian government had reasons of its own–not “good” reasons from an economic efficiency perspective, but political reasons–to impose an export ban.  Hence, I think that Oganev’s plea probably didn’t affect the Russian government in any way.  But it is unethical for a firm with a position to advocate wasteful policies that would tend to favor that position, and an export ban would have done just that.  Advocating wealth-destroying policies is hardly laudable either, position or no.

Commodity trading and processing firms are notoriously opaque–precisely because they make money on the information they generate in their operations, and have every incentive to hold that information very tightly.  This story provides a very revealing glimpse at what goes on in those firms.  It is a particularly interesting example of the synergy between the operation of physical assets and trading operations.

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