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Interactive analysis

Commodity Price & Cost Risk

Explore feed-ingredient prices and stress-test a purchasing budget.

USDA ERS · Monthly dataThrough August 2026Released September 14, 2026Sources & methodology ↓

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About the analysis

Sources & methodology

Data preparation, risk analysis, and interactive visualization by Wajdi Belgacem.

Download analysis code (ZIP) ↓

Public data and price definitions

Monthly prices come from USDA ERS Feed Grains Yearbook Tables 12 and 16. Corn is No. 2 yellow in Central Illinois. Soybean meal is the Central Illinois high-protein series. Current underlying AMS definitions are delivered truck bids for corn and FOB rail asking prices for soybean meal. These are distinct market benchmarks, not a matched delivered quote for one business.

Coverage: January 2000–August 2026. USDA release: September 14, 2026. Data accessed: September 20, 2026. Prices are in nominal U.S. dollars and are subject to revision.

Prices reflect the USDA release shown above and are monthly benchmarks, not live market quotes.

Price comparisons, volatility, and missing data

Corn is converted from dollars per bushel to dollars per U.S. short ton using 56 pounds per bushel and 2,000 pounds per short ton. A metric tonne is 1,000 kilograms; one pound is 0.45359237 kilograms. The indexed chart sets each series to 100 in the first month of the selected period. The benchmark table always uses the most recent month with both prices.

Historical volatility is the sample standard deviation of consecutive monthly log price changes, multiplied by √12 and expressed as a percentage. It changes with the selected history window. It measures past variability, not the probability or size of a future loss.

Soybean meal has no observation in November 2004, September 2019, or October 2019. Those values remain blank. Lines break at missing months, and returns that cross a missing observation are excluded from volatility calculations. No interpolation is used.

Cost scenarios and interpretation

Baseline cost is the sum of quantity × (reference price + freight/handling adjustment). Scenario cost is the sum of quantity × [reference price × (1 + price change / 100) + adjustment]. Quantities are monthly and stay fixed between the baseline and scenario. Changing the quantity unit converts the inputs to preserve the same physical amount and total cost.

Quantities and price changes are user-defined. The sensitivity comparison holds quantities, the reference month, and delivery adjustments fixed.

Results cover ingredient purchasing costs and the delivery adjustments entered. They exclude other operating costs, revenue, hedging, taxes, and financing, so they do not measure profitability.

Data sources and code