ianmadlenya Goto Github PK

followers: 152.0 following: 828.0 repos: 2.7K gists: 23.0

Name: Ian Madlenya

Type: User

Bio: Highly analytical & process-oriented Data Analyst with in-depth knowledge of database types; research methodologies; and big data capture, curation/manipulation

Location: Ireland

Blog: www.linkedin.com/in/ianmadlenya

Ian Madlenya's Projects

elementor

The most advanced frontend drag & drop page builder. Create high-end, pixel perfect websites at record speeds. Any theme, any page, any design.

elitequant

A list of online resources for quantitative modeling, trading, portfolio management

C/C++ 11 High frequency quantitative trading platform. It follows modern design patterns such as event-driven, server/client architect, dependency injection and loosely-coupled robust distributed system. It is self-contained and can be used out of box. At the same time, it serves as server side for other EliteQuant projects.

elitequant_matlab

Matlab quantitative trading and investment platform. EliteQuant_Matlab is Matlab based multi-threading, concurrent high-frequency trading platform that provides consistent backtest and live trading solutions. It follows modern design patterns such as event-driven, server/client architect, and loosely-coupled robust distributed system. It follows the same structure and performance metrix as other EliteQuant product line, which makes it easier to share with traders using other languages.

elitequant_python

Python quantitative trading and investment platform; Python3 based multi-threading, concurrent high-frequency trading platform that provides consistent backtest and live trading solutions. It follows modern design patterns such as event-driven, server/client architect, and loosely-coupled robust distributed system. It follows the same structure and performance metrix as other EliteQuant product line, which makes it easier to share with traders using other languages.

elitequant_r

R quantitative trading and investment platform. EliteQuant_R is R based multi-threading, concurrent high-frequency trading platform that provides consistent backtest and live trading solutions. It follows modern design patterns such as event-driven, server/client architect, and loosely-coupled robust distributed system. It follows the same structure and performance metrix as other EliteQuant product line, which makes it easier to share with traders using other languages.