Blind faith: Why following commodity forecasters is a bad idea

We all like to read forecasts of what the future holds. But, in the case of the outlook for commodity prices is following the lead of one commodity forecaster or another just blind faith?

Over at Cullen Roche’s excellent Pragmatic Capitalism blog, Cullen illustrates a point about the multitude of articles about how bearish George Soros is on a particular asset market. Cullen goes onto say how this could potentially lead individual investors into trouble.

In all seriousness, the key lesson here is that we need to be very careful about how much we read into news headlines about market gurus. It’s very easy to get swept up in the idea that a wealthy investor knows more than the rest of us and that we should follow their disclosed moves as reported and after the fact. The financial media loves to use big names to grab headlines and page views. But in many cases you’re not getting the full story about what this investor is doing. And following their supposed positioning could lead to bad decisions and unnecessarily poor performance.

In the case of commodity markets blindly following forecasts from one or another investment bank could equally lead to bad decisions. I’ve no reason to pick on them, but Goldman Sachs is often thought of a the ‘guru’ in commodity markets.

Should you just follow them blindly and invest? No, absolutely not. First, you don’t know what level of risk they are taking to enter that position, have they hedged it and how etc? The best investors should also be able to change their minds if the evidence no longer supports their original hypothesis. Will that change in view then get picked up by the press? It might do, but it might not.

Think about why forecasts are published by the press. Are they to help inform those not fortunate enough to be able to afford buying forecasts off the shelf from one or another bank or consultancy? Or are they meant as ‘entertainment’, as a way of gathering publicity in order to sell other services?

We, as investors, business people tend to like the story, the narrative that can explain how things develop. To put structure to the apparent uncertainty and volatility going on in the world. We like stories, we like to summarize, we like to be able to reduce a complex interaction of multiple factors into a single sentence sound-bite, eg “Lower, for longer”. As Nichola Taleb points out this fallacy “distorts our mental representation of the world; it is particularly acute when it comes to the rare event.”

The same goes for forecasters. In relatively benign market conditions there is something of an institutional inertia – only updating their view of the world slowly and iteratively, not wanting to appear to far from the pack or consensus. The exception to this appears to be when markets reach a peak or a trough in short order. Here investment banks, commentators, etc all want to come up with an even more extreme prediction of where prices could go, in order to make a name for themselves.

In 2008 it was Goldman’s and their $200 per barrel call on oil. In late 2014 and into early 2015 it was most notably Goldman Sachs highlighting the risk of $20 oil, others then jumped on the bandwagon as prices fell and their forecasts of $18 per barrel no longer seemed as far fetched.

There is also a time inconsistency. Relatively specific forecasts are often matched with an unspecific time frame, which also makes it difficult to score them for accuracy. There is a maxim among professional analysts that cynically confirms the problem: always predict a price, or a time-frame, but never both. However, in recent years, many oil market forecasters have been pushed to quantify their forecasts by making specific price predictions over specified time horizons.

Whats needed is a way to verify the accuracy of commodity forecasts. Verifying accuracy is obviously much easier for weather forecasts, where thousands of fresh forecasts are issued every day, and sometimes even more frequently, and can be compared with thousands of outcomes. Verification is more difficult for subjects like oil prices,but given how frequently prices are forecast it is not impossible and would be highly desirable.

One of the major problems with any verification approach though comes back to time. Given that commodity cycles can typically last somewhere between 5-15 years we are still scratching the surface of a reliable period of back data.

Arguably, what is most important to commodity producers and consumers is not having a forecast of future commodity prices but understanding the risk that prices will go to extreme levels, either high or low during a particular period and the impact this could have and what can be done to mitigate it if it does.

All of which means that investors and physical buyers and sellers will continue to rely on ‘guru’s’ to some extent. Demand forecasts if you have to. But demand better forecasts.

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