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Energy Price Forecast

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Databricks2024-05-09 收录
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https://marketplace.databricks.com/details/91ac0139-7129-48a8-ba9f-dc0989774013/S-P-Global-Commodity-Insights_Energy-Price-Forecast
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**Overview** The Energy Price Forecast dataset provides access to the latest energy price forecasts and historical prices across 9 different commodity groups. Leverage this dataset to improve trading strategies, investment decisions, and risk management with access to short-term price forecasts available up to 36-months out and long-term price forecasts available up to 30-years out, depending on commodity group. Users can also better understand evolving market dynamics with access to historical cases to compare how outlook has evolved over time. This dataset includes: - Historical coverage provided monthly and annually from 1995, depending on commodity group - Monthly forecast data available through the end of Platts Analytics' short-term forecast period (between 12 and 18 months or 36 months for some commodity groups) - Annual forecast data available through the end of Platts Analytics' long-term forecast period (between 15 and 20 years) - Coverage of Oil (Crude Oil and Refined Products including NGL), Americas and European Gas, Americas and European Power, LNG, Coal, Agriculture (Biofuels), Energy Transition (Greenhouse Gas, North American Emissions and RECs) **Use cases** - Fundamental Analysis - Assess long-term trends of commodity price forecasts to determine where best to invest - Market Analysis - Better understand evolving market dynamics with access to historical cases to compare how outlook has evolved over time - Pricing Analysis - Quickly identify arbitrage opportunities by analyzing historic and forecast spreads between domestic sourced and imported gas, coal, and oil products. Rapidly perform a comparison between refined oil products, gas and coal where there is an option to switch fuels - Risk Analysis - Improve trading strategies, investment decisions, and risk management with access to short-term price forecasts available up to 36-months out and long-term price forecasts available up to 30-years out, depending on commodity group **Product details** Sample Tables: A ) PRICES_LONGTERM B ) PRICES_SHORTTERM Sample Fields: A ) PRICES_LONGTERM YEAR CATEGORY_NAME GROUP_NAME PRICE_NAME PRICE_SYMBOL PRICE UNIT_NAME UNIT_ID CURRENCY_SYMBOL CURRENCY_DESCRIPTION B ) PRICES_SHORTTERM YEAR MONTH CATEGORY_NAME GROUP_NAME PRICE_NAME PRICE_SYMBOL PRICE UNIT_NAME UNIT_ID CURRENCY_SYMBOL CURRENCY_DESCRIPTION View Descriptions: - PRICES_LONGTERM - Platts latest long-term price forecasts and historical prices provided on a yearly granularity - PRICES_LONGTERM_ARCHIVE - Archived long-term price forecasts - PRICES_SHORTTERM - Platts latest short-term price forecasts and historical prices provided on a monthly granularity - PRICES_SHORTTERM_ARCHIVE - Archived short-term price forecasts - REF_DATA_CATEGORIES - List of commodity groups supported based on user's subscription - REF_DATA_COMMODITIES - List of commodities associated with prices - REF_DATA_CURRENCIES - Provides a collection of currencies available in the dataset - REF_DATA_DELIVERY_REGIONS - List of delivery regions associated with prices - REF_DATA_GROUPS - List of price groups supported in the dataset based on user's subscription - REF_DATA_LONGTERM_ARCHIVE_DATES - List of dates long-term forecasts were modified - REF_DATA_LT_YEARS - List of years price data is available for long-term forecasts and historical prices - REF_DATA_PRICES - List of prices supported based on user's subscription - REF_DATA_SECTORS - List of sectors supported in the dataset based on user's subscription - REF_DATA_SECTOR_GROUPS - List of sector groups associated with prices - REF_DATA_SHORTTERM_ARCHIVE_DATES - List of dates short-term forecasts were modified - REF_DATA_ST_YEARS - List of years price data is available for short-term forecasts and historical prices - REF_DATA_UNITS - List of physical units supported in the dataset - ENERGYPRICEFORECAST_DICTIONARY - Contains descriptions and examples of each of the columns in the above views for a better understanding of the dataset
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S&P Global Commodity Insights
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