MATLAB Computational Finance Suite

Develop and scale computational finance models

The MATLAB Computational Finance Suite is a set of 12 essential products that enables you to develop quantitative applications for risk management, investment management, econometrics, pricing and valuation, insurance, and algorithmic trading.

The suite is offered as an annual license at a discounted package price.

With the MATLAB Computational Finance Suite, you can:

  • Chart historical and live market data
  • Perform time-series analysis and create predictive models
  • Model interest rates and perform sensitivity analyses on financial instruments
  • Solve portfolio optimization problems and perform risk attribution
  • Develop quantitative models to optimize performance and minimize risk
  • Integrate with data sources and legacy software
  • Develop and deploy applications to production environments, desktops, servers, and the web (deployment requires additional products)

MATLAB Computational Finance Suite Product Set


Develop algorithms, create custom visualizations, and automate workflows.

Curve Fitting Toolbox

Fit curves and surfaces to data using regression, interpolation, and smoothing.

Database Toolbox

Exchange data with relational and non-relational databases.

Datafeed Toolbox

Access financial data from data service providers.

Econometrics Toolbox

Model and analyze financial and economic systems using statistical methods.

Financial Instruments Toolbox

Design, price, and hedge complex financial instruments.

Financial Toolbox

Analyze financial data and develop financial models.

Optimization Toolbox

Solve linear, quadratic, integer, and nonlinear optimization problems.

Parallel Computing Toolbox

Perform parallel computations on multicore computers, GPUs, and computer clusters.

Risk Management Toolbox

Develop risk models and perform risk simulation.

Spreadsheet Link (for Microsoft Excel)

Use MATLAB from Microsoft Excel.

Statistics and Machine Learning Toolbox

Analyze and model data using statistics and machine learning.

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