About

Priyharsh Gangwar is a highly skilled and experienced Quantitative Researcher with a background in Civil Engineering and additional courses in Computer Science and Bio-Science. He holds an MS in Quantitative Economics from ISI-D and an MS in Financial Engineering from WQU, as well as a Bachelor of Technology degree from IIT Bombay. With a strong interest in Quantitative Finance and Algorithms, Data Analysis and Visualization, Chess, Equity Markets, and Biomimetics, Priyharsh has worked as a Quantitative Researcher at Trexquant Investment, where he has been responsible for researching financial literature and diverse datasets to identify novel alpha signals to achieve high Sharpe Ratios and significant abnormal returns. He has also developed algorithmic long-short trading strategies in US, European, and Asian equity markets, working with multiple datasets such as Fundamental, Technical, News, and Alternative data to create mid-frequency Alpha signals. Prior to his work at Trexquant Investment, Priyharsh worked as a Python Developer at Its Planners and Engineers, where he used Python and TraCI library to alter traffic signal phases to give priority to emergency vehicles, achieving up to 50% reduction in average waiting time for emergency vehicles at the cost of 10% increment in average waiting time for other vehicles. He was also responsible for creating road networks of multiple cities using NETEDIT to analyze traffic behavior and the impact of intersections and diversions. Priyharsh's experience also includes serving as the Institute Chess Club Manager at The Dark Knight Chess Club. He possesses a strong tech stack, including Research Scientist, Python, and Android. With almost four years of relevant experience, Priyharsh is a highly motivated and skilled professional who is committed to delivering high-quality work and achieving exceptional results.