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Do you know the huge hidden pitfalls of commodity price forecasts?

Unless you’ve been living on the moon, you will know by now that the price of oil has dropped substantially.

If you’re a regular reader of or financial articles in general, you’ll also know that ratings agency Standard & Poor’s has lowered its forecasts for oil prices several times in the past few months, delivering a credit rating downgrade to Aussie producer Santos Ltd (ASX: STO) in the process.

Future credit rating changes may or may not be forthcoming for other Australian producers like Woodside Petroleum Limited (ASX: WPL), Origin Energy Ltd (ASX: ORG), and Oil Search Limited (ASX: OSH).

Those credit ratings – and thus the value of shares and cost of a company’s debt – depend in a large part on the assumptions of the future oil price from rating agencies.

I personally use these assumptions as little more than an indicator of market sentiment, however they are widely covered in the media and often treated as gospel and forecasts, despite the fact that they are neither, often inaccurate, and prone to change on a monthly basis.

As one of the most visible ratings agencies, Standard & Poor’s (S&P) serves as a good example of the inscrutability of these assumptions.

Here’s a quick compilation of what that agency’s oil assumptions looked like in recent months (All prices refer to Brent Crude oil, listed in US$/ barrel).

S&P forecast made in June 2014 S&P forecast made in Nov 2014 S&P forecast made in Dec 2014 S&P forecast made in Jan 2015
Average prices forecast for 2014 $110 $85 $75
Average prices forecast for 2015 $105 $90 $80 $55
Average prices forecast for 2016 $100 $90 $85 $65
Average prices forecast for 2017
and beyond
$95 $90 $85 $80

It is important to note that these are price assumptions, not forecasts. They are an expectation of where a commodity price will be based on prevalent market dynamics at the time the assumption is made.

Furthermore, they are only as good as the formula used to develop them.

For widely traded commodities like oil and gas, Standard and Poor’s methodology uses the futures curve ‘as the starting point for our pricing assumptions’ and also uses ‘market indicators’ and some qualitative factors in its short-term (year 1 and 2) pricing analysis.

As readers can clearly see, this is borne out in the table. Back in June 2014 when all was fine and dandy, Brent Crude oil futures were trading around $110 per barrel. S&P’s oil price forecast for June 2014? $110 per barrel.

In November, futures prices dropped to ~$84 a barrel. S&P’s forecast? $85 a barrel.

December 2014 futures were trading at $80 each (forecast $75). October 2015 futures are hovering around $56 a barrel (forecast $55), and February 2016 futures are trading for around $47 (forecast $65).

While S&P may well use its own methodology, the fact that its short-term assumptions change to match futures prices bring into question the real value of these figures.

Since futures generally follow market perception of what’s going to happen with the oil industry, Standard and Poor’s closer targets are effectively mirroring market sentiment and ‘groupthink’ rather than providing independent commentary.

S&P even goes so far as to state that if there “is at least a 20% difference between our futures prices and our near-term pricing assumptions and we view the difference to be sustainable, then we will typically modify our assumptions.”

This is why forecasts have changed so rapidly over the past few months, since OPEC declared its intentions not to cut production to support prices. In S&P’s defence, this is not something that could reasonably be predicted. However, long-term forecasts are equally problematic.

Long-term (two year and longer) forecasts use ‘Market- and issuer-specific supply and demand fundamentals’ as well as examining spare capacity, cost curves in the industry, and internal price expectations used by companies in their forward-looking plans.

While S&P’s current (Jan 2015) long-term forecasts for 2016 look more accurate than February 2016’s futures prices, for instance, the analysis of future supply and demand did not lead researchers to draw the same price conclusions in November and December as they did in January.

In the final two months of last year oil was still forecast to be at US$90 and US$85 a barrel in 2016 despite it becoming apparent that there would be a significant surplus due to rising US production and OPEC maintaining production targets.

Now all of a sudden in January, a little over 30 days later, oil is predicted to be US$20 a barrel lower in 2016 than was forecast in December. Supply and demand cannot have changed so drastically in that time.

It’s not the only time S&P has got their long term price assumptions wrong, with a January 30, 2014 update assuming prices of  US$110/$100 per tonne for iron ore in 2014 and 2015 despite ample evidence that massive oversupply was coming.

I personally wrote an article in December 2013 suggesting that prices would fall in 2014 (although not to the magnitude that they did), and Motley Fool analyst Scott Phillips beat me to the punch by more than two years, calling an iron ore bubble way back in September 2012.

Sure enough, the commodity came unravelled partway through 2014, and now trades for US$70 per tonne.

Two weeks after Mike King’s article on the fall was published, Standard and Poor’s released updated price assumptions of US$95 per tonne for 2014, 2015, and 2016.

This certainly raises some questions for the validity of ratings agencies price assumptions, doesn’t it?

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Motley Fool contributor Sean O'Neill doesn't own shares in any company mentioned.

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