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Schematic (not to scale) Time Price
Fundamental Analysis Commodities

Seasonal Agricultural Patterns

Learn why agricultural commodities are seasonal, when weather risk is highest, and how stocks-to-use ratios change price sensitivity.

Key takeaways

  • Seasonality creates predictable ‘risk windows’.
  • Low inventories make markets more sensitive to weather/yield shocks.
  • Traders focus on expectations for acreage, yields, and final production.

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Visual map

Use the diagrams to translate the narrative into a simple question: what changed versus expectations, and does it make the market tighter or looser?

Panel 1: Risk window Planting Growing season
weather risk Harvest
Panel 1: Weather risk is highest during the growing season; harvest brings supply clarity.
Panel 2: Stocks-to-use Lower stocks → higher sensitivity
Panel 2: When inventories are low, small yield surprises create outsized price moves.

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Key concepts (with meaning and application)

Each concept is written as a practical trading tool: definition → why it moves prices → how you use it.

Crop calendar (planting → harvest)

What it means: A seasonal sequence that determines when supply is set and when uncertainty is highest.

Why it matters: Weather and planting decisions create uncertainty; price reflects risk premium before harvest clarity.

How to apply it: Know the key months for each crop and treat those periods as higher volatility regimes.

Acreage and yield

What it means: Acreage is how much is planted; yield is output per acre.

Why it matters: A small change in acreage or yield can materially change total supply.

How to apply it: Build scenario ranges: ‘normal’, ‘good weather’, ‘stress’ yields and map price sensitivity.

Stocks-to-use

What it means: Inventory relative to expected consumption.

Why it matters: Lower stocks-to-use means less buffer; price becomes more sensitive to surprises.

How to apply it: When stocks-to-use is low, reduce size and expect bigger reactions to weather reports.

Basis and spreads

What it means: Local pricing and futures spreads reflect short-term tightness and storage costs.

Why it matters: Spreads often tell you whether the physical market is tight (backwardation) or loose (contango).

How to apply it: Use spreads as confirmation: if spreads tighten alongside bullish news, the signal is stronger.

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How to apply this to trading

How to apply this to trading

  • Identify the crop’s ‘risk window’ (planting/growing season).
  • Track expectations: acreage estimates, weather outlook, and early yield indicators.
  • Use inventory tightness (stocks-to-use) to judge how much the market should move on news.
  • Confirm with spreads and physical indicators when possible.

Example

If stocks-to-use is low and a drought develops during the growing season, futures can rally sharply as the market prices a yield loss. If late-season rains recover yield, the rally can unwind quickly.

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Common mistakes

  • Ignoring seasonality and expecting steady behaviour year-round.
  • Treating early-season forecasts as final yields.
  • Forgetting that substitution and demand rationing can cap rallies.
  • Overtrading weather headlines without confirmation.

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FAQ

Why do agricultural markets react so much to weather?

Because weather directly affects yields, and supply is fixed once the crop is grown.

What is the best single tightness metric?

Stocks-to-use is widely used because it captures buffer relative to demand.

Do prices always rise on bad weather?

Not always. If the market already priced the risk, the reaction can be muted or reversed.

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Summary

  • Commodity prices are driven by supply, demand, inventory, and expectations.
  • Watch the key marginal driver: production decisions, storage, weather, and global growth.
  • Manage risk around scheduled reports and sudden supply shocks.

Last updated: 2025-12-28 (UK time).