Trexquant Investment LP
Peng Gong has held various roles in both the finance and academia sectors. Peng started working as a Quantitative Portfolio Manager at Trexquant Investment LP in February 2016 and later became the Director of Research in January 2018. Prior to that, they worked at Carnegie Mellon University as a Graduate Teaching Assistant from January 2013 to January 2016, teaching courses on Data Mining and Structural Health Monitoring. Peng also served as a Graduate Research Assistant at the university from September 2012 to January 2016, conducting research on interpreting ultrasonic signals for damage detection in engineering structures.
Peng Gong obtained a Bachelor's Degree in Civil Engineering from Dalian University of Technology in 2010. Peng further pursued their studies and completed a Master's Degree in Civil Engineering from the same institution between 2010 and 2012. Recognizing their passion for academic pursuits, they pursued a Doctor of Philosophy (Ph.D.) in Civil Engineering at Carnegie Mellon University from 2012 to 2016.
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Trexquant Investment LP
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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.