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Agrinvest Commodities & Consultoria — Historical Brazilian cash-market (physical) commodity quotations exposed through a documented, filterable API. Each record is a five-key observation: quotation date (dt_date), city/state (city_st), commodity, spot-versus-forward flag (info_ship), shipment period as month/year (ship), and price value. Commodities documented: soybean, corn, soybean meal, soybean oil. The city x date x forward-shipment-period structure means the series support basis construction against CBOT, forward-book price discovery by delivery month, and city-to-city differential analy…
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Historical Brazilian cash-market (physical) commodity quotations exposed through a documented, filterable API. Each record is a five-key observation: quotation date (dt_date), city/state (city_st), commodity, spot-versus-forward flag (info_ship), shipment period as month/year (ship), and price value. Commodities documented: soybean, corn, soybean meal, soybean oil. The city x date x forward-shipment-period structure means the series support basis construction against CBOT, forward-book price discovery by delivery month, and city-to-city differential analysis — the shipment-period field in particular captures the physical forward curve, which is rarely available outside bespoke vendor feeds.
Scale Not stated on the pageFrom 20 yearsCoverage Financials · Consumer Staples
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Agrinvest Commodities & Consultoria — Historical Brazilian cash-market (physical) commodity quotations exposed through a documented, filterable API. Each record is a five-key observation: quotation date (dt_date), city/state (city_st), commodity, spot-versus-forward flag (info_ship), shipment period as month/year (ship), and price value. Commodities documented: soybean, corn, soybean meal, soybean oil. The city x date x forward-shipment-period structure means the series support basis construction against CBOT, forward-book price discovery by delivery month, and city-to-city differential analy…
Agr offers (Price, Alternative, Supply Chain) — Not stated on the page, but bounded from the schema: at daily cadence across an unprinted city list and 4 named commodities with spot and forward records, order 10^5-10^6 observations per year (e.g. 40 cities x 4 commodities x ~250 days x spot + forward bookings). Request the true row count and city list as the first scoping question..
Brazilian physical-basis modelling: city cash price against CBOT soybean and corn futures to derive and forecast origin basis; construction of the physical forward curve by shipment month, which futures alone cannot provide; crush and crushing-margin modelling across soybean, meal and oil simultaneously at the same city; interior-versus-port and city-to-city differential (freight-implied) analysis; producer sales-timing and cooperative pricing tools; hedge-ratio calibration for B3 and CBOT positions referencing real physical prices; and training data for commodity price models needing granular, location-tagged targets.
The data is with 20 years of history.
Coverage spans Other, US; Financial Exchanges & Data, Agricultural Products & Services; price, alternative, supply_chain; commodities, futures, equities.
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