How accurate are your commodity price predictions?

Helios’ price forecasts are up to five times more accurate than traditional industry models, which have historically relied only on seasonality trends and basic supply/demand figures.

On average, Helios models are 108% more accurate than standard naive and OLS models, with the highest performing model outperforming the naive basis by 565.15%. By integrating climate risk indicators, regional production data, and real-time market signals, we deliver forecasts that help procurement leaders and traders stay ahead of market volatility.

This higher accuracy translates directly into better margins and reduced exposure to unexpected price swings—whether you’re timing a futures position, negotiating contracts, or securing supply in a tight market. With Helios, you’re not just reacting to the market—you’re anticipating it.

Unlike providers that rely solely on market price patterns, Helios incorporates climate risk signals, production forecasts, and supply chain indicators into our models. This gives us an informational edge—our price predictions often detect turning points earlier, particularly in ag commodities where weather shocks and yield swings play a huge role.

Because our data is fully cleaned, normalized, and standardized, we remove the noise and inconsistencies that can distort forecasting models. This is especially important in commodities where pricing terms (FOB, DDP, EXW) or market locations can create misleading comparisons if not harmonized.