Crude Forecasts: Predictions, Pundits And Profits In The Commodity Casino by Peter Sainsbury

Author:Peter Sainsbury [Sainsbury, Peter]
Language: eng
Format: epub
Published: 2017-11-10T00:00:00+00:00

The final type of herding is known as investigative herding. Investigative herding arises when investors trade similarly by reacting to the arrival of a commonly observed information signal. Analysts have an incentive to investigate a piece of information or a market that he knows other analysts may also investigate and trade in. From the point of view of getting a return on the forecast, there is no incentive to build a position in a particular market if other investors won’t join on the same side and push the price in the direction of the forecast. Illiquid markets tend to be less well served precisely because it is not worthwhile for banks and other financial institutions to trade them. It follows that the reputational risk of making forecasts about illiquid and volatile commodity markets is much higher.

A market for lemons?

There is another factor to consider when thinking about forecasts. Again it comes down to the incentives of the forecaster, but this time the inference is more insidious. The nature of forecasting may drive out those that are best equipped to produce them. Commodity price forecasts might just be a market for lemons. This reference to lemons comes from economist George Akerlof, who published a paper in 1970 in the Quarterly Journal of Economics called “The Market for Lemons”. Within it was a simple and revolutionary idea in which he noted that markets in which buyers possess imperfect information while sellers possess a profit motive are thin, insubstantial and low quality.[67]

Akerlof used the example of the used-car market. Suppose buyers in the used-car market value good cars – referred to as “peaches” – at $20,000, while sellers value them slightly less. A malfunctioning used car – a “lemon” – is worth only $10,000 to buyers (and, again, assume a bit less to sellers). If buyers can tell “lemons” and “peaches” apart, trade in both will flourish. In reality, buyers might struggle to tell the difference: scratches can be touched up, engine problems left undisclosed, even odometers tampered with.

To account for the risk that a car is a lemon, therefore, buyers cut their offers. They might be willing to pay, say, $15,000 for a car they perceive as having an even chance of being a “lemon” or a “peach”. But dealers who know for sure they have a “peach” will reject such an offer. As a result, the buyers face “adverse selection”: the only sellers who will be prepared to accept $15,000 will be those who know they are offloading a “lemon”.

Smart buyers can foresee this problem. With the knowledge that they will only ever be sold a “lemon”, they offer only $10,000. Sellers of “lemons” end up with the same price as they would have done were there no ambiguity. However, the “peaches” stay in the garage. This is a tragedy: there are buyers who would happily pay the asking price for a “peach”, if only they could be sure of the car’s quality. This “information asymmetry” between buyers and sellers kills the market.

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