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Oil market takes a walk on the wild side (again)

Oil market takes a walk on the wild side (again)

The current surge in volatility seems to owe more to internal market factors than external fundamentals, writes Reuters’ columnist John Kemp

Crude oil prices have been on a rollercoaster over the last few trading sessions that has seen some of the highest volatility in a quarter of a century.

The market is providing a brutal reminder of the extreme side of commodity pricing, leaving many analysts and traders struggling to identify a safe strategy.

Front-month Brent crude futures rose by more than 10 per cent on Thursday (August 27), 5 per cent on Friday (August 28) and 8 per cent on Monday, before plunging by more than 8 per cent on Tuesday.

To put that in context, the percentage daily price movements were 4.6 standard deviations away from the mean on Thursday, 2.4 standard deviations on Friday, 3.7 on Monday and 3.8 on Tuesday.

If price changes followed a normal distribution, a move of 3.5 standard deviations should occur only once every eight years and a move of greater than 4.5 standard deviations should happen once every six centuries.

The occurrence of three exceptional moves in the space of just four trading sessions underscores changes in oil prices do not follow a normal or Gaussian distribution, named after the 19th century mathematical genius Carl Friedrich Gauss.

Even though they are taught that it is not an accurate description of how financial markets work, the normal distribution exerts a strong unconscious influence on how traders, analysts and investors think about the risk of extreme price moves.

But it significantly understates the probability of very large price movements and is little use in understanding how commodity markets behave. Commodity markets are much more dangerous than the comforting world of the Gaussian distribution allows.


The extreme movement of commodity prices was first observed in the early 20th century by Wesley Mitchell and Frederick Mills.

But it was rediscovered and made famous by Benoit Mandelbrot in the 1960s, who studied cotton prices and discovered far more large moves than expected if they followed a normal distribution.

As Mandelbrot explained, the normal distribution “does not account for the abundant data (on price changes) accumulated since 1900 by empirical economists.”

He went on to observe “empirical distributions of price changes are usually too peaked to be relative to samples from Gaussian populations.”

There are “so many outliers” and “the tails of the distributions of price changes are in fact so extraordinarily long” they could not be modelled by a normal distribution.

In simple terms, large price changes occur much more frequently than if commodity prices followed a normal pattern.

In technical terms, the distribution of price changes is leptokurtic, with more extreme events in the tails than are found in Gaussian distribution.

In Brent, prices have moved by more than three standard deviations up or down on about 100 days since 1990, or roughly four times per year. If they were Gaussian this should have happened only once every 17 months.

Four standard deviation moves have occurred on roughly 37 days since 1990, or about once every year and a half, when if they were Gaussian such a move would have occurred only once in 60 years.


Mandelbrot’s other insight was to realise that the average level of volatility in commodity prices is not constant over time. The level of volatility is itself volatile.

Moreover, the level of volatility tends to “cluster”. Time series of commodity prices show periods of low volatility alternating with periods of much higher volatility.

Commodity markets swing from a mild state to a wild one and back again, Mandelbrot wrote.

Brent prices confirm the essential truth of Mandelbrot’s observation about volatility clustering.

The market is currently in a “wild” phase in which volatility is elevated with a series of unusually large price moves coming one after another.

Other volatility clusters can be identified in early 2015 (associated with rising oil stocks); May 2011 (oil market flash crash); October 2008 to March 2009 (global financial crisis); September 2001 to February 2002 (attack on the World Trade Centre), 1998 (Asian financial crisis); and August 1990 to March 1991 (first Gulf war).

Once the market is in a wild state, the probability that one large daily move will be followed by another is much higher than usual, until the market settles down into a calm state again.

Phase shifts from mild to wild and back again are typically abrupt and are difficult if not impossible to predict in advance.

Before Mandelbrot, some economists claimed daily price moves could be divided into ordinary random movements (in the quiet periods) and larger purposeful movements “traceable to well-determined causes” (the wild periods).

But it is not obvious that this is a good description of the way markets work and Mandelbrot himself was sceptical.

Some periods of high volatility are clearly associated with observable external factors (recessions and wars). But others lack an obvious external source and seem to be generated by the positioning of traders within the market (including the May 2011 flash crash).

The current surge in volatility seems to owe more to internal market factors, especially the race to cover hedge fund short positions built up between June and August, than external fundamentals.


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