Seasonal Forward Curve

The seasonal forward curve is a forward curve that repeats a distinctive humped or gapped pattern year over year, driven by the calendar cycles of production, harvest, and demand. Agricultural commodities, natural gas, and electricity show the pattern most clearly, embedding the full annual storage and convenience-yield cycle into contract prices.

The annual storage cycle

A grain farmer harvests corn in September and October. The entire annual supply arrives within weeks. Demand, however, spreads across all twelve months—millers, ethanol plants, and livestock operations need steady feed. The market must therefore store the harvest and release it gradually. The forward curve embeds the full cost of that holding.

Just before harvest, September futures trade at a peak. The old crop is now scarce; storage vaults are nearly empty. Convenience yield is high—owners of physical inventory can command a premium. December futures, a few months after harvest, trade lower because supply will be ample and storage will be in heavy use. Then, as the curve extends further out, contracts rise again as the next harvest approaches and the previous crop ages in storage, accumulating carrying costs.

This creates a characteristic bowl-shaped or sawtooth pattern. The curve drops from old-crop to new-crop contracts, then rises again as time passes and storage days accumulate. The pattern repeats each year, and sophisticated traders exploit it ruthlessly.

Why storage costs create the hump

The cost of carry formula drives this pattern. Just after harvest, supply is abundant and storage costs are low per unit (elevator capacity is not fully used). Forward contracts reflect this surplus, trading at modest premiums to spot. As months pass and the crop is consumed, supply tightens. Those who own grain must keep it in vaults—the storage bill accumulates. By mid-season, when inventory is falling but storage days have mounted, the cumulative carry cost is highest. Contracts maturing near harvest (the next crop) trade at steep premiums.

Then, as the next harvest nears, those steep premiums collapse. Farmers planting the new crop know that large supply is coming; physical holders of old grain lose their scarcity premium. Basis traders—firms that own elevators and storage—profit by buying cheap new-crop futures and selling expensive old-crop futures, then holding the physical spread as the market rebalances.

Agricultural commodities: the clearest example

Corn and soybeans show the seasonal pattern most starkly. US corn harvests in September–October, yielding supply that must carry through to the next August. March futures (winter storage) trade significantly higher than December futures (early new crop). December, in turn, trades higher than November (harvest month). The forward curve for months 12–24 (the following year’s crop) typically starts flat and low, then gradually rises as storage days accumulate—a mirror of the first cycle.

Wheat seasonality is similar but offset by different harvest months in different regions. Winter wheat harvests in May–June in the US; spring wheat in September. Winter wheat futures curve shows a low point in May–June (abundant supply) and a peak the following March–April (before the next harvest). The markets must account for all this in real time.

Soybeans harvest only once per year (September–November), creating the starkest seasonal curve. March or May soybeans (deepest into carry) trade substantially above November (harvest month). A basis trader who buys November futures and sells May futures locks in the full carry curve—essentially financing the crop from harvest through the next spring.

Natural gas and electricity seasonality

Energy commodities have different drivers but follow the same logic. Natural gas demand spikes in winter (heating) and summer (air conditioning). Production, however, is relatively steady. A seasonal forward curve for natural gas shows peaks in January and July–August, with troughs in May–June and September. Storage (in vast underground caverns) is a critical infrastructure; the curve reflects when gas must be injected into storage (pricey, because demand is low) and withdrawn (valuable, because demand is high).

Electricity cannot be stored efficiently, so its seasonality is even sharper. Peak-hour contracts trade vastly higher than off-peak. Seasonal transmission congestion—when summer heat hits California or winter cold hits the Northeast—creates dramatic spikes in forward prices. The curve is not smooth but jagged, with sharp peaks around known stress periods and flat troughs around periods of abundant supply and low demand.

Convenience yield swings with scarcity

Underlying the seasonal curve is a convenience yield that swings with supply scarcity. When new crop is abundant, convenience yield is low—owning physical inventory has little value. When old crop is running out and the next harvest is months away, convenience yield spikes; a miller holding safety stock of raw material avoids the risk of stockouts. This shifts the entire forward curve.

In years of supply shock—a drought cuts corn yields, or a production outage hits a refinery—the seasonal pattern distorts dramatically. Convenience yield jumps, contango flattens, and sometimes flips to backwardation. The curve loses its typical bowl shape and becomes inverted, signalling acute scarcity.

Basis trading and the curve

Basis traders and elevator operators profit by understanding seasonal curves better than the general market. A grain elevator operator knows the exact cost of storing corn for six months. If the forward curve suggests a storage premium larger than the operator’s actual costs, buying cheap nearby futures and selling expensive deferred futures is pure arbitrage. If the premium is too low, the operator simply holds cash grain (storing physically) instead of selling it forward.

This activity keeps the curve honest. The seasonal pattern is real but contestable—each year, basis traders arbitrage away parts of it, flattening peaks and raising troughs. Yet the core structure persists because the underlying supply-demand calendar never vanishes.

Why forecasting seasonal curves is hard

The seasonal pattern is predictable in structure but not in magnitude. A drought or a bumper crop can double or halve the storage premium. A sudden demand shock (a feed mill switches suppliers, a bioethanol plant shuts) changes the curve shape within days. Financial traders and producers must constantly recalibrate their expectations.

Yet the seasonal curve is one of the most profitable patterns in commodities. Funds and dealers build quantitative models to track it, and vast capital sits in seasonal trades—buying the cheap new-crop contract and selling the expensive old-crop contract, over and over, across all storable commodities. The pattern is real. The margin is often thin. But the consistency pays.

See also