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_excel

EliteQuant Excel for Quantitative Modeling, Trading, and Portfolio Management. It enables you to create quantitative financial models in Excel spreadsheet, in the same way how financial professionals such as traders, quants, and portfolio managers do their day to day work. You are able to create pricing tools for products across all asset classes such as interest rate or FX, and from plain vanilla to exotic instruments. You are also able to backtest and live trade from Excel, with the so-called RTD, or real-time data support.

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.