Being a quantitative finance firm that uses Machine Learning (ML) to create multi-asset portfolios and seek profit from the market, Trexquant has continuously improved its investment and research platform since starting operations, leveraging new and emerging technologies. Trexquant uses rigorous quantitative methods to create multi-asset portfolios in global markets. To do this, Trexquant develops trading signals using its vast and continuously growing collection of data variables used as inputs for more complex trading models called Strategies. The result is an ever-growing and adapting engine built from thousands of intricate models and tens of thousands of signals, tailor-made with the goal to outperform the market during any condition. Capital is managed across 5,500+ cash equity positions across the United States, Europe, Japan, Australia, and Canada.

Trading & Exchanges

Trexquant Investment LP

Tyger Park

Cara C.

Sujay Prasad Srivastava

Peng Gong

Denis Lapitski

Michael Marinic

Isabelle Chan

Kyle Nemchek Cfa

The Quantitative Research Team at Trexquant Investment LP conducts cutting-edge research to develop and refine sophisticated trading models and strategies. Leveraging advanced statistical methods and machine learning techniques, the team analyzes extensive datasets to generate actionable trading signals that inform multi-asset portfolio management. By continuously exploring new data variables and optimizing existing models, the team plays a crucial role in enhancing the firm’s ability to outperform the market across various economic conditions.

Quantitative Research Team

Finance and Strategy Team

Engineering Team

Quantitative Research Team

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Team members

Other teams at Trexquant Investment LP

Finance and Strategy Team

Engineering Team