Finance & Banking Data Analytics with GAUSS

Main Applications of GAUSS in Finance

The GAUSS platform provides a powerful and efficient environment for analyzing financial data. GAUSS provides easy-to-use, pre-built financial analysis tools for every stage of your finance project from data wrangling and cleaning to forecasting and reporting.

GAUSS is used in a variety of theoretical and empirical finance applications including quantitative asset management, risk parity, option pricing and hedging, financial risk management, exchange options, and more.

Whether you are just in the beginning stages of data wrangling, cleaning, and visualization or the final stages of estimation and financial forecasting, GAUSS supports your financial data analysis needs.

Time Series, Regression Models and Other Main Functions of GAUSS for Finance

Data cleaning, processing, and management

General Statistical Analysis

Pre-built GAUSS functions can be used to efficiently and intuitively implement fundamental econometric models including:

Time Series Analysis

With GAUSS time series analysis is made easy and efficient whether you're just getting started or developing new cutting edge methods. GAUSS time series capabilities include:

GAUSS Applications Designed for Finance


Time series MT

Includes comprehensive tools for time series data analysis including
  • MLE and state-space estimation
  • Unit root and cointegration testing
  • Model diagnostics and forecasting
  • Nonlinear time series models

Linear regression MT

Provides procedures for estimating single equations or systems of equations including:
  • Two-stage least squares.
  • Three-stage least squares.
  • Seemingly unrelated regression.

Fanpac MT

Provides econometric tools commonly implemented for estimation and analysis of financial data:
  • Allows users to tailor each session to their specific modeling needs.
  • Includes tools for modeling univariate and multivariate Generalized Autoregressive Conditionally Heteroskedastic (GARCH) models.

Maximum Likelihood MT

Provides a suite of flexible, efficient and trusted tools for the solution of the maximum likelihood problem with bounds on the parameters. Includes:
  • Variety of descent and line search algorithms.
  • Analytical and numerical derivatives.
  • Dynamic algorithm switching.
  • Multiple tools for statistical inference.

Constrained Maximum Likelihood MT

Provides a suite of flexible, efficient and trusted tools for the solution of the maximum likelihood problem with general constraints on the parameters. Features include:
  • Linear and nonlinear equality and inequality constraints.
  • Trust region method.
  • A variety of descent and line search algorithms.
  • Analytical and numerical derivatives.
  • Dynamic algorithm switching.
  • Multiple methods for statistical inference.

Optimization MT

Optimization MT provides tools for efficient optimization including:
  • Select descent algorithms.
  • Step-length methods.
  • Algorithm switching.

Constrained Optimization MT

Solves the nonlinear programming problem, subject to general constraints on the parameters. Includes:
  • Linear or nonlinear constraints.
  • Equality or inequality constraints.
  • Uses sequential quadratic programming method in combination with several descent methods.
  • Trust region method.

Descriptive Statistics MT

Provides basic statistics for the variables in GAUSS datasets. These statistics describe and test univariate and multivariate features of the data and provide information for further analysis.

Algorithmic Derivatives

Provides tools for computing algorithmic derivatives.
  • Works independently of other applications.
  • Can be used with any application that needs derivatives.
  • The use of algorithmic derivatives can improve accuracy and convergence speeds.

Industries that use GAUSS Data Analysis Tools

GAUSS is used across a number of industries for financial data analysis. GAUSS is found in

  • Universities
  • Government agencies
  • Non-governmental organizations
  • Nonprofit research organizations
  • Corporations

Whether your goal is forecasting financial outcomes, hedge fund management, portfolio optimization, or teaching future financial analysts, GAUSS offers the tools you need to succeed.

Icons of some organizations where GAUSS is used.

Benefits of GAUSS for Finance

GAUSS provides a fast and flexible environment for financial data analysis. Whether you are performing ordinary least squares regressions or developing cutting-edge algorithms, GAUSS provides tangible advantages including:

  • Over 1000 pre-built statistical and econometric functions.
  • Light-weight and efficient analytics engine designed to make the most of your hardware and provide optimized computation speed.
  • Intuitive matrix-based programming language for transparent and easy to understand programming.
  • Fully interactive environment for speeding up your workflow from exploring data to analyzing results.
  • Comprehensive documentation and examples.
  • Comprehensive data support including CSV, Excel HDF5, SAS, Stata, text delimited files.
  • Relational database support including MySQL, PostgreSQL, SQLite, Microsoft SQL Server, Oracle, IBM DB2, HBase, Hive and MongoDB.

Compatibility of GAUSS with Other Software

GAUSS is built to seamlessly integrate into any analytics environment:

  • GAUSS is fully compatible with SAS, STATA, HDF5, CSV, and Excel datasets.
  • Efficiently connect powerful analytics to any internal or customer-facing data source, application, or interface with the GAUSS Engine.
  • Full technical support for assistance when migrating from and integrating with other software platforms.

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