ARGUS Possibility Curves

What is the volatility and balance of risk for energy and commodities prices?

Data-driven insights and market context are needed to address this seemingly simple question, yet this answer can give you an edge in making better, faster trading, hedging and risk management decisions.

Argus Possibility Curves estimate the pair of probability and energy prices, as well as the volatility and balance of risk (asymmetry in the upside or downside risk) so that you can:

  • Identify trading signals missed by other sources
  • Drive systematic trading models using unique, alternative data
  • Get market insight distinct from what is found in traditional fundamental analysis

Why Argus Possibility Curves?

Our curves pair unique data and market knowledge, with data science expertise.

Alternative physical transactions data. We couple conventional financial and macroeconomic drivers with proprietary data garnered from our role as a price reporting agency. Because Argus crude oil prices are used in over 90pc of physically-indexed trade and virtually all swaps contracts in the US Gulf coast and Cushing, we have the most complete data set of actual deals and historical prices for US crude markets.

Energy and commodity markets are at our core. Since 1970, Argus has produced price assessments and analysis of international energy and other commodity markets. This expertise allows us to give real market context to the data.

How does it work?

Argus Possibility Curves

Argus Possibility Curves are developed with the leading feature engineering, feature selection (including key drivers) and model diagnostics processes, building on decades of market expertise and machine learning algorithms.

In essence, Argus Possibility Curves can be used to develop trading and risk management tools such as trading scorecards based on the latest market dynamics that can measure:

  • Price volatility: Fast-moving markets can result in exciting trading opportunities
  • Balance of risk (upside vs downside risk): These infrequent, big market changes can shift the P&L

Because the forward-looking Argus Possibility Curves cover up to three months ahead, scorecards can be developed for crude grades, time spreads and grade spreads.

See the ARGUS Possibility Curves in action

Argus Data Science Studio

Financial institutions, trading houses and physical buyers and sellers around the world are using the Argus Data Science Studio to reveal the uncertainties and volatility associated with commodity prices.


  • Machine learning framework

    Our machine learning framework includes the use of linear and non-linear relationships, interactions between market drivers and the power to handle relatively small datasets. It also includes a suite of model diagnostics to dynamically monitor the performance of the possibility curves and better capture changes in crude markets.
  • The data and determining key drivers

    Our curves utilise Argus’ proprietary deals and pricing data, augmented with publicly-available fundamentals, financial and macroeconomic data filtered through our market-informed feature engineering process. The model’s key drivers are reassessed daily.
  • The output

    Our machine learning framework estimates an array of possibilities as a primary output. Key features of the output include more accurate possibility intervals for prices (for example, there is a 50% chance that the price is between $53.00/bl and $54.40/bl) and better quantification of balance of risk (for example, changes in the asymmetry of upside or downside risk based on prevailing market conditions).


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