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Platts Market Data - Coal

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Snowflake2022-07-07 更新2024-05-01 收录
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https://app.snowflake.com/marketplace/listing/GZTSZ1389NW
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Platts coal price assessments are essential to give you insight into the true market value of coal as well as an understanding of the reasons behind market shifts. But in this increasing complex trading environment, understanding the correlation between regions and markets, in order to compete effectively has never been more important. Platts Market Data - Coal package provides access to the full breadth and depth of our coal market data, including benchmarks and contract price assessments, plus: - A robust, transparent and proven methodology allowing you to access the best possible reflection of market value, on the day, in a variety of regions - Historical data to enable you to look at past market trends to inform your future plans and back testing needs Coverage includes: - Daily and weekly assessments and indexes for international coal trading - Nearbys - NYMEX data for Central Appalachian coal - Futures - NYMEX data for Central Appalachian coal - Asia Pacific and Atlantic thermal coal - Southeast Asia Thermal coal marker (SEAT) - Northeast Asia Thermal coal Index (NEAT) - European Blended Price (EBP) - Central Appalachian (CAPP) - Powder River Basin (PRB) - Illinois Basin US thermal coal netbacks for FOB US East Coast: - FOB US Gulf Coast - FOB Vancouver FOB export assessments for: - FOB Baltimore - FOB Hampton Roads - FOB New Orleans - FOB Long Beach - FOB Oakland - FOB Vancouver <p><br/></p> Sample Tables:<br/>A ) PRICEDATA<br/>B ) REF_DATA_MARKETDATA Sample Fields:<br/>A ) PRICEDATA - SYMBOL - MDC - DESCRIPTION - BATE - ASSESSDATE - UOM - CURRENCY B ) REF_DATA_MARKETDATA - COMMODITY - DELIVERY_REGION - DESCRIPTION View Descriptions: - PRICEDATA - Get the latest and historical assessments by Symbol - CORRECTIONS - Get all corrections to the assessments by Symbol - REF_DATA_MARKETDATA - Get additional reference data for Symbols - MARKETDATA_DICTIONARY - Contains descriptions and examples of each of the columns in the above views for a better understanding of the dataset
提供机构:
S&P Global Energy
创建时间:
2022-06-29
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