The calculation of damages in various types of disputes in the natural resources sector (eg, expropriations in investor-state arbitrations) frequently requires expert evidence on the valuation of a mine, or oil and gas field. Such valuations often include discounted cashflow (DCF) models, where the experts forecast future cashflows with reference to the expected future price of a commodity.
The availability of different sources of information means that the respective experts sometimes rely on commodity price forecasts which are very different, and since DCF valuations are typically sensitive to even small differences in such forecasts, the experts may arrive at very different conclusions on value. Therefore, arbitrators often need to consider the relative merits of different commodity price forecasts, given the facts of each case.
Tethyan Copper v Pakistan
In this case the claimant’s valuation expert valued a pre-production copper and gold mine at USD 8.5 billion, using a DCF model with price forecasts based on the traded prices for copper and gold futures contracts. However, when Pakistan’s valuation expert replaced these prices with consensus price forecasts for copper and gold, which were based on individual price forecasts from independent commodity price analysts, the claimant’s DCF model then produced a negative value of USD1.5 billion (ie, a difference of USD 10 billion between the experts). The tribunal valued the mine at USD 4.1 billion, which was based on the claimant’s DCF model, adjusted for the impact of various risks identified by the respondent.
As illustrated in Tethyan Copper and many other valuation disputes in the natural resources sector, there are two main approaches for obtaining commodity price forecasts – traded futures prices and consensus price forecasts.
Traded futures prices
Commodity futures contracts represent a commitment to buy or sell a commodity for a specified price at a particular future date. For example, copper futures are traded on exchanges such as the Commodity Exchange (COMEX) and the London Metals Exchange (LME). A forward curve shows the relationship between the price of futures contracts and the time to maturity of that contract.
Futures contracts may be sold by commodity producers (such as a copper-mining company selling copper futures to guarantee sales prices to service its debt) or bought by consumers (such as an airline buying crude oil futures to hedge against rising fuel costs). Financial institutions such as investment banks and hedge funds also typically trade futures contracts in large volumes.
One of the key advantages of using forward curves as commodity price forecasts is that they're traded in real time and react quickly to supply or demand shocks. For example, following Russia’s full-scale invasion of Ukraine, the Brent crude oil spot price increased from around USD 95 per barrel on 24 February 2022 to around USD 128 per barrel by 8 March 2022, a 25% increase, with an associated adjustment to futures prices.
However, while futures contracts for short maturities (eg, crude oil in three months) are generally traded in large volumes, trading volumes for long maturities (eg, crude oil in five years) are often much thinner. In practice, such illiquidity means that investors are generally sceptical that futures prices are a reliable indicator for long-term commodity prices.
Consensus price forecasts
Consensus price forecasts are usually calculated as the mean, or median, of a set of independent forecasts from investment banks and economic consulting firms. Commodity analysts generally base their price forecasts on a detailed analysis of expected future supply and demand for each commodity. Such analysis typically involves the use of industry ‘cost curves’ which graph the production costs of a particular commodity, beginning with the lowest-cost producers and then moving through progressively higher-cost producers. In simple terms, the highest cost producer in a particular demand-scenario sets the price for that commodity. For example, if copper demand is expected to be 35 million metric tonnes in five years’ time, then the price of copper needs to be at least equal to the production cost of the marginal tonne, otherwise that tonne wouldn't be produced.
Consensus price forecasts may be obtained from various sources: Consensus Economics surveys more than 40 energy and metals analysts for a range of approximately 50 commodities, setting out quarterly price forecasts for the next two years; annual average forecasts for the next five years; and a long-term average forecast for five to ten-year prices.
Bloomberg also compiles consensus price forecasts from a range of independent commodity analysts. The default Bloomberg consensus price forecasts take the median price forecasts from analysts who have updated their price forecasts in the last six months and shows price forecasts for the next four quarters; and yearly price forecasts for as long as analysts have estimates for.
Rockhopper v Italy
Parties to a dispute sometimes reference in-house price forecasts from major commodity producers. For example, in Rockhopper v Italy, the claimants noted that their valuation expert used a price forecast that was more conservative than oil giant BP’s long-term oil price. However, such forecasts aren't independent and are generally excluded from any analysis of consensus price forecasts for independent valuations.
A key disadvantage of using consensus price forecasts is that some commodity price analysts may be slow to update their forecasts following supply or demand shocks. Therefore, it may be necessary to make further adjustments to a simple mean, or median, calculation, for example, by excluding crude oil price forecasts that predated a particular event such as the onset of COVID-19 or Russia’s full-scale invasion of Ukraine.
Sensitivity of DCF valuations
Given the sensitivity of DCF valuations to changes in commodity price forecasts, valuation experts may wish to provide a sensitivity analysis to assist the tribunal in understanding how valuations vary according to different price forecasts, and other key inputs such as discount rates.
However, providing too much variation to the inputs in such an analysis may be counterproductive if it leads to a very wide valuation range. For example, in Rockhopper, the claimants’ valuation expert valued the subject asset (a pre-production oil and gas field) at EUR 275 million using a DCF analysis. The claimants also presented a 'pre-tax high case' valuation of EUR 1.5 billion and a low valuation of EUR 68 million which Italy argued only illustrated the speculative nature of the claim. The tribunal elected not to use the claimants’ DCF model but instead chose to use an earlier DCF model which Rockhopper had prepared for its decision to acquire the subject asset, which valued the asset at EUR 184 million.
Next steps
Overall, it's generally best practice for experts to consider more than one source for commodity price forecasts in valuation disputes. Experts should evaluate the strengths and weaknesses of traded futures prices and consensus price forecasts on a case-by-case basis, consider factors such as the liquidity of long-term traded futures prices and the ability of commodity price analysts to react quickly to sudden changes in supply or demand. Tribunals may find a DCF sensitivity analysis helpful, although experts should be careful that different combinations of inputs don't produce an extreme valuation range.
For more insight and guidance, get in touch with Paul Cliff or Ryan Boorman.
