EconoMonitor

Oil Prices and Trading Mechanics

A report from Reuters (hat tip: Felix Salmon) attributes the wild commodity price moves last week to algorithmic stop-loss trading.

Jim Brown offered these details on the oil trading:

Those funds interviewed said the massive amount of stop losses that were triggered was beyond comprehension…. When the crash finally came the number of positions liquidated was staggering. As each technical level was broken it triggered more stop losses and more short selling to capture the drop….

Credit Suisse analysts said the high frequency and algorithmic trading accounted for about half of all the volume in the oil markets.

Every day, futures prices can and do move in response to how many people want to buy or sell the contracts. As I explained in a recent study in Brookings Papers on Economic Activity, inventory arbitrage forces the spot price to move along with the futures price. But as I also explained there, this does not mean that sentiment or speculation alone can put the price of oil at any arbitrary value. Ultimately, the critical question is whether the spot price is one at which the physical quantity produced is equal to the physical quantity consumed. Whether today’s price indeed accomplishes this was the focus of my discussion of these events last weekend.

But clearly, there are lots of big traders out there who are thinking not along these lines but rather in terms of Keynes’ beauty contest, supposing that all that matters is guessing what other people think the price will be, and fooling themselves into believing that by programming their computers to buy high and sell low they are going to outsmart the other players.

Count me among those who maintain that buying high and selling low is unlikely to be a successful trading strategy. But if enough people believe otherwise, they can wreak a bit of havoc on the rest of us before they themselves go belly up.

hamilton_oil_51311.jpg 


This post originally appeared at Econbrowser and is reproduced here with permission.

One Response to “Oil Prices and Trading Mechanics”

GuestMay 13th, 2011 at 12:44 pm

At the March IMF conference on “Macro and Growth Policies in the Wake of the Crisis” one of the panel participants (I forget which panel) said the he had just found out, to his surprise, that traders were developing predator algorithms design to identify trade algorithms, learn their trigger rules, then exploit them. I filed it as Quants 2.0. I was expecting you to go in that direction.

Most Read | Featured | Popular

Blogger Spotlight

Ed Dolan Ed Dolan's Econ Blog

Edwin G. Dolan is an economist and educator with a Ph.D. from Yale University. Early in his career, he was a member of the economics faculty at Dartmouth College, the University of Chicago, and George Mason University. From 1990 to 2001, he taught in Moscow, Russia, where he and his wife founded the American Institute of Business and Economics (AIBEc), an independent, not-for-profit MBA program. Since 2001, he has taught at several universities in Europe, including Central European University in Budapest, the University of Economics in Prague, and the Stockholm School of Economics in Riga, where he has an ongoing annual visiting appointment. During breaks in his teaching career, he worked in Washington, D.C. as an economist for the Antitrust Division of the Department of Justice and as a regulatory analyst for the Interstate Commerce Commission, and later served a stint in Almaty as an adviser to the National Bank of Kazakhstan. When not lecturing abroad, he makes his home in San Juan Islands, Washington.

Economics Blog Aggregator

Our favorite economics blogs aggregated.