Rapidly develop new models and deploy them to analysts and traders. Power front-to-back trading systems with instant computations and real-time data feeds.
From exploring market behavior to managing portfolios, the Mathematica financial engineering solution provides state-of-the-art calculations and easy connectivity to databases and web services, as well as high-performance computing with built-in parallel processing that scales to a full grid.
Exploring new theories of market behavior
Interactive tool showing a rule diagram for a trader model with three choices: buy, sell, or hold
Performing powerful symbolic and numeric calculus and statistical computations
Moving averages of Apple's stock price calculated by interactively varying the smoothing parameter
Using built-in financial data or bringing in data from other sources
Predicting changes in the price trend of an asset with divergence tracking
Financial engineering and mathematics specific capabilities:
Flexible platform for rapid development and exploration of financial models, with hundreds of highly efficient built-in algorithms relevant to quantitative research
Powerful symbolic statistical computation and built-in functions for all standard statistical distributions Competitor note: Advanced symbolic computational capabilities are unique to Mathematica
Gain accuracy and reliability by performing symbolic calculations, not just numeric ones Competitor note: Matlab's and Java's built-in routines only handle numeric calculations
Having an integrated environment streamlines development, analysis, documentation, and delivery of custom financial models Competitor note: Traditional programming languages like C/C++ don't have all the built-in computations and capabilities of Mathematica
KEY CAPABILITIES
WHY CHOOSE MATHEMATICA
WAYS TO USE
Search for patterns in past data, develop algorithms to predict future market movements, and deploy them as tools for traders
Mathematica rapidly prototypes products and trading strategies for the world's largest market maker in Eurodollar derivatives
Develop new theories to explain market efficiency
Build artificial markets to model agent behavior
Ensure accuracy by backtesting trading strategies and stress testing product models
"The amount of code that's required to produce the same amount of work is a fraction of the amount of code that we would have to write with other tools, so the time to delivery is much faster."
—Alan Savoy
Technical Manager and Architect, nGenera Corporation
INTERACTIVE FINANCIAL ENGINEERING AND MATHEMATICS EXAMPLES