High performance math libraries
for real-time computing

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Why Choose RTMath?

Outstanding Performance

Outstanding Performance

All complex computations are amplified by state-of-the-art libraries: Intel® Math Kernel Library, Intel® Integrated Performance Primitives (IPP), LibSVM, Shark, BOOST and others. Special engineering helps to achieve the lowest possible friction cost and deliver native performance without losses.

Real-Time Computing

Real-Time Computing

RTMath was initially designed for efficient real-time computations on financial markets. Interfaces produce minimal or zero garbage and allow to quickly re-estimate parameters of quantitative models based on the latest observations.

Cost-Efficient Full Pack

Cost-Efficient Full Pack

RTMath products offer a full set of tools that may be required for heavy math-focused applications development: from linear algebra and statistics to machine learning and competitive numerical solvers. With RTMath you can save time and effort spent on purchasing, studying, and integration of multiple libraries and concentrate on your core tasks.

Powerful and Easy-to-Use APIs

RTMath offers simple object-oriented APIs, identical in C# and Java. APIs cover most scientific complexities by default for fast and easy prototyping and on the other hand offer a vast variety of tuning options to achieve the maximum precision when solving specific tasks. Rich documentation and handy samples make RTMath adoption quick and easy.

What is RTMath?

What is RTMath?

RTMath provides a set of .NET and Java components and libraries for numerical calculations, time-series data analysis and visualization. Based on very efficient integration with Intel® Math Kernel Library (MKL) and Intel® Integrated Performance Primitives (IPP), RTMath components are highly-optimized, extensively-threaded math routines that provide outstanding performance and scalability. RTMath components offer both ultra-fast execution and efficient memory usage.

All RTMath components provide excellent computational efficiency and memory utilization, they are easy to use, and well documented. The installation includes API references with the description of classes and class members combined with detailed code samples.


FinMath is a highly-optimized numerical library that provides components for the development of mathematical, scientific, and financial applications on the .NET platform. It offers classes for working with vectors and matrices, solving optimization problems, random number generation, statistical analysis, option valuation and other uses. FinMath combines a broad range of functionality, outstanding efficiency, and modern easy-to-use object-oriented interface.

Go to FinMath page
FinAnalysis chart


FinAnalysis is a comprehensive .NET library of technical indicators, predicates, and generic-purpose classes for real-time data analysis. It includes 40+ advanced technical indicators and 15+ logical predicates for expressing relationships between two or more time-series data sets. FinAnalysis is optimized for performance classes for processing large quantities of real-time and historical time-series data with built-in correlation analysis and calculations of descriptive statistics.

Go to FinAnalysis page

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RTMath vs Competitors:

RTMath computational features ensure an outstanding performance and efficient memory usage due to highly efficient integration with Intel® libraries. RTMath products are benchmarked against competition. Special attention is paid to the ease of integration of RTMath with your applications.

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RTMath vs Competitors

Boost Productivity

RTMath components are successfully used in research and production by many high frequency stat arb & algorithmic trading organizations working in the global equity, futures, forex and option markets.

RTMath components enable you to express your ideas faster, optimize your code and increase the overall productivity of your research with modern user-friendly interfaces of RTMath. Enjoy its full power and flexibility.

“The FinMath library provides a comprehensive set of tools for our research and its execution efficiency impressed us. Excellent product, highly recommended.”
Huabin Shen,
Bond Trust
Customer Quotes
“Excellent product, highly recommended”