Sent: 09-12-2011 14:15:03
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Why Picking Commodities Doesn't Work
THE chance of an investor consistently picking mining stocks based on a view about relative commodity price movements may be close to zero.
Within the stockbroking community, large volumes of research are produced highlighting the likely trajectory of commodity prices. Using this material, analysts continually express their "preference" for one metal over another.
With their metal price views come stock recommendations. If they forecast zinc prices to rise faster than copper or nickel prices, for example, they will recommend buying Global Zinc and lightening exposure to Universal Copper and Galaxy Nickel. Journalists, thinking there must be some sense to all this work, dutifully report the emerging consensus that zinc prices are going to rise faster and that Global Zinc is the stock most brokers are recommending.
The chief executive of Global Zinc, meanwhile, is on a roadshow to persuade investors that zinc market balances are becoming more attractive, trying to leave the impression that prospective investment returns from his company will be better, too.
The brokers, the journalists and the executives are all basing their expressions of opinion on the assumption that forecasts can be made accurately, disparate movements in commodity prices occur frequently and are likely to persist long enough for the equity market to react positively.
To test the proposition, E.I.M. Capital Managers reviewed historical data for a range of commodity prices over the last 30 years. The following commentary, using copper, zinc and nickel prices, illustrates the key elements of the analysis.
Between the beginning of 1980 and July 2011, copper prices rose at an annual rate of 4.3%. Zinc prices increased at a 3.7% rate and nickel prices rose at 4.2% a year. In other words, over the long haul, differences in commodity price movements are not great enough to offer a meaningful guidepost for equity (or commodity) investors.
To assess the frequency with which meaningful price performance deviations might arise within this time frame, we counted the instances of copper, zinc or nickel price outperformance. We measured how many times movements in the price of each metal exceeded movements in the price of either of the other two by more than 20% over a six month period. (The standard deviation in returns ranged from 33%pa for copper and 38% for zinc, to 57% for nickel.)
Based on this analysis, we can say there was a meaningful deviation in commodity price returns 52% of the time. Not surprisingly, given their relative volatility, nickel prices were the most likely to display a meaningful performance difference from time to time.
Persistence of price effects is likely to be important for equity markets which will usually begin to factor into stock prices a continuation of strong commodity prices only after some accumulated evidence about the likelihood of the change persisting.
To assess the chance of the price strength persisting, we looked at how frequently the outperforming price was higher 12 months later. We found a 48-50% chance of price strength persisting.
To follow through on this, we need an initial price forecast. Of course, this is easier said than done as many academics, policymakers and market analysts have demonstrated. One study touching on this that comes to mind is a working paper by two International Monetary Fund economists (Chakriya Bowman and Aasim M Husain) published in 2004.Their measures of forecasting performance suggested a random walk model was just as, if not more, useful.
In June this year, two Federal Reserve Bank of New York economists (Ian J J Groen and Paolo A Presenti) wrote that "the results look almost random" and that "forecasts of commodity prices provide only highly noisy hints about their actual future trajectories and persistence".
So, let's assume that our in-house professional commodity price forecaster is one of the best in the business and that he gets his metal price forecasts right about 60% of the time - more often than the studies suggest is humanly possible.
- My forecaster has a 60% accuracy rate;
- There is a 52% chance of a meaningful price difference emerging; and
- There is around a 50% chance of the price effect persisting in a way that might lead to an impact on equity markets.
This suggests a meagre 16% chance that all three stages line up; that I can get a good forecast of a meaningful and persistent price deviation. If I took a more realistic view of my forecaster's accuracy, that chance might be more like 10% or lower.
So, I am about to take an equity investment decision based on nothing more than 'a highly noisy hint', according to people who have looked at this thoroughly, and I have not given any thought, as yet, to which stock to buy.
Let's say we buy Global Zinc based on our commodity price forecast for zinc.
As it happens, the Global Zinc mine site has been subjected to historically unprecedented heavy rainfall recently. Who would have guessed because there is no news coverage on this - the newspapers and business magazines have all been about the strength of the zinc market.
Two days later, the sodden mine site slides down from its elevated mountain location never to be seen again. The subsequent environmental litigation and arbitration over compensation for the surviving members of the local valley communities is expected to go on for 20 years. The resulting production fall causes the zinc price to rise, happily reinforcing the reputation of my commodity price forecaster. My equity portfolio returns look less encouraging.
A rhetorical question: against this background, how much analytical effort should I put into my price forecasting for individual commodities (and, by the way, how much emphasis should Global Zinc place on its commodity positioning when its executives try to persuade me of its investment attractiveness)?
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