Key Impact Points:
- Analyst carbon price forecasts typically have a 35.5% error rate over 12 months, according to DWS.
- Carbon price forecasts influence major industrial investments, potentially misallocating capital if predictions are inaccurate.
- Forecasting accuracy is significantly worse for carbon markets compared to similarly volatile assets like U.S. natural gas.
Forecast Reports Flood the Market
By December, investment banks and financial institutions inundate investors with predictions for the next 12 months. Bloomberg estimates that banks released 650 such reports for 2024, and the signal-to-noise ratio continues to deteriorate.
Rupak Ghose highlights this trend: “Wall Street analysts love writing tomes for their outlook pieces with lots of verbose language to illustrate how they are intellectuals and not salespeople.” However, these reports primarily serve as marketing tools, not reliable guidance.
The Role of Carbon Price Predictions
Carbon markets are increasingly critical for companies and investors managing decarbonization strategies. Accurate forecasts shape decisions for power generators and industrial emitters:
- Overestimated prices can drive premature investments with suboptimal returns.
- Underestimated prices delay essential investments, risking compliance costs later.
Investors, too, are swayed. Bullish predictions, such as those in late 2021, prompted investors to buy carbon futures, anticipating rising prices.
Accuracy of Carbon Price Forecasts
DWS examined analyst forecasts from 2010 to 2021 and found a 35.5% average error rate for carbon prices.
- In comparison, assets with similar volatility, like U.S. natural gas, showed significantly lower error rates.
- High price volatility exacerbates forecasting errors, yet carbon markets fare worse than gold, copper, and crude oil.
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Broader Forecasting Trends
Peter Sainsbury, author of Crude Forecasts, found similar errors in oil price predictions:
- WTI crude 6-month consensus forecasts (2007-2016) had a 27% error rate.
- 12-month oil price forecasts were only slightly worse at 30%.
Sainsbury underscores incentives as a core driver of forecasting trends. As Warren Buffett puts it: “Forecasts usually tell us more of the forecaster than the future.”
Incentives Driving Forecasting Behavior
- Safety in Numbers: Analysts stick close to consensus predictions, especially when markets experience sustained highs or lows. Extreme peaks and troughs often trigger exaggerated bullish or bearish forecasts.
- For example, during the early 2000s commodity super-cycle, predictions turned increasingly optimistic.
- Conversely, in 2016, bearish projections proliferated as oil prices hit a trough.
- Anti-Herding: Research from the European University Viadrina Frankfurt analyzed over 20,000 forecasts for metal prices (1995-2011). Instead of herding behavior, they identified a trend of anti-herding – where forecasters intentionally deviate to appear contrarian.
Bottom Line
Carbon price forecasts are influential but deeply flawed, with a high average error rate that complicates investment decisions. Investors and industries should approach predictions cautiously, balancing market sentiment with robust, long-term strategies.
