The Wolfram Solution for

Financial Risk Management

Rapidly develop and test robust financial risk models and deploy them as interactive applications or as high-performance infrastructure components—all from one system, with one integrated workflow.

The Wolfram financial risk management solution is unique in offering the reliability of a mixed symbolic-numeric approach to computation, multiple switching algorithms, built-in computable financial and economic data, and built-in parallel computation for scaling up.

Using built-in or imported financial data in risk modeling
The Wolfram Edge
How Wolfram Compares
Key Capabilities

Mathematica includes thousands of built-in functions and curated data on many topics that let you:

  • Develop and refine analytic models for risk
  • Back-test trading strategies to check viability, or stress test models to account for extreme market changes
  • Access real-time trading data and perform instant analysis
  • Calculate value-at-risk for different portfolios and time horizons
  • Do straight-through processing from the trade capture to the backend
  • Create new tools for calculation, graphing, and modeling and deploy them to your website
  • Immediately compute with data from your existing Bloomberg feeds
  • Dispatch order routing on .NET and Java platforms from one central command center
  • Perform position reconciliation with online statements from the clearinghouse with XML functions

Easily flow live Bloomberg desktop data into any computation or visualization with Wolfram Finance Platform

Instantly create sophisticated financial charts from built-in data feeds

Next: How Wolfram Compares
The Wolfram Edge
How Wolfram Compares
Key Capabilities

Does your current tool set have these advantages?

  • Symbolic capabilities of time-value and bond functions allow for seamless integration with Mathematica's statistics framework for use in financial computations involving uncertain outcomes
  • Develop, analyze, test, document, and deliver custom models in a fraction of the time needed with other systems
  • Get accurate results with fully automated precision control and arbitrary-precision arithmetic
    All systems relying on machine arithmetic, such as Excel or Matlab, become inaccurate
  • Gain accuracy and reliability by performing symbolic calculations, not just numeric ones
    Matlab's built-in routines only handle numeric calculations
  • Choose from procedural, functional, and rule-based programming paradigms for fast development and deployment
    Other computation environments use predominantly procedural languages

Present results in reports and slide shows containing interactive tools

Use modernized versions of classic financial charts such as three-line break, point-figure, Renko, and Kagi charts

Next: Key Capabilities
The Wolfram Edge
How Wolfram Compares
Key Capabilities

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