Natural Gas Intelligence is a subscription service. If you are interested in receiving NGI natural gas and LNG pricing indexes, data and news, or need additional information, please contact sales@naturalgasintel.com.
Weekly Historical Data
Weekly historical natural gas pricing data dating back to 1989
RECOMMENDED FOR:
- Natural gas buyers and end-users
- LDCs, utilities and electric generators
- Government and regulatory agencies
- Accounting, settlement, compliance and risk professionals
- Midstream Companies
HOW TO ACCESS:
- Web access
- Datafeed file, NGI Data Services API and Excel Add-in
- NGI delivery platform partners
- Enterprise subscriptions available
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A reliable and affordable indicator of weekly movements in natural gas pricing across the U.S. and Canada, NGI's Weekly Historical Data provides key understanding of weekly prices going back to 1989.
Weekly Historical Data:Weekly historical natural gas pricing data dating back to 1989
WHY SUBSCRIBE:
- Historical database of spot natural gas prices (weekly averages) at 170+ locations across the U.S. and Canada
- Most pricing data points dating back to 1989
- Referenced in dozens of FERC jurisdictional natural gas pipeline company "cash-out" tariffs
- Published prices include deals from the Intercontinental Exchange (ICE), as well as Price Reporter data direct from companies principal to deal
- Data are available in easy-to-use formats, allowing users to save hours of data entry and reducing risk of mistakes
- Access to price analysts and exceptional customer service
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Industry News & Basic Data
Weekly Gas Price Index
- Spot natural gas prices (weekly averages) at 170+ locations across the U.S. and Canada
- Referenced in dozens of FERC jurisdictional natural gas pipeline company "Cash-Out" Tariffs
- Published prices include deals from the Intercontinental Exchange (ICE), as well as "Price Reporter" data direct from companies principal to the deals
Indicative Data
Forward Datafeed
- Daily forward curves expressed as both fixed prices and basis differentials to the Henry Hub
- Curves published as both individual months and seasonal strips
- Curves going out 10 years at 70+ locations
Updated Pricing
Weekly Datafeed
- Database of spot natural gas prices (weekly averages) at 170+ locations across the U.S. and Canada
- Published prices include deals from the Intercontinental Exchange (ICE), as well as “Price Reporter” data direct from companies principal to the deals
- One of only two price reporting agencies that include Intercontinental Exchange (ICE) data in price methodology
Weekly Historical Data FAQ
How do I get NGI pricing data and news?
How does NGI’s price index methodology compare to others in the market?
Natural Gas Intelligence is one of only two price reporting agencies that has access to Intercontinental Exchange (ICE) trade data, which supports a robust and market-driven price index. NGI uses transactions from ICE along with reported prices to arrive at its daily, weekly and bidweek price indexes. Find out more about NGI’s price index methodology here.
On which days does NGI publish prices?
NGI publishes daily, weekly and monthly (Bidweek) pricing data, as well as forward curves. To find out specifics, our Publishing Calendar can be found here.
In what forms can I access NGI content?
NGI content is delivered via e-newsletters and the NGI website. Additionally, most NGI content is available in PDF for read-only use. For data consumption, NGI provides web and API delivery mechanisms, as well as third-party channel partners. For more information, contact sales@naturalgasintel.com.
Why does it matter that NGI has Intercontinental Exchange (ICE) trade data?
NGI is one of only two price reporting agencies that include ICE transactions to determine its natural gas indexes. ICE is an electronic trading platform where the bulk of physical and financial natural gas trades are done for North America. By incorporating ICE trade data with NGI-reported company trades, NGI is able to provide more representative and transparent pricing data. Find out more about NGI’s price index methodology here.