Many quantitative firms have suffered substantial losses as a result of the COVID-19 selloff, but very few market makers experienced similar impact - as they turned to nowcasting for managing real-time risks.
In this webinar Marcos Lopez de Prado will highlight three lessons that quantitative researchers could learn from this episode based on his latest SSRN paper developed in collaboration with Alexander Lipton - "Three Quant Lessons from COVID-19". Marcos will also share his research on Estimation of Theory-Implied Correlation Matrices introducing applications of knowledge graphs for machine learning (ML).
This webinar is brought to you by Thinknum Alternative Data and is a part of a series of global volatility virtual events featuring thought leaders in finance, machine learning and data.
Our expert Prof. Marcos López de Prado is the CIO of True Positive Technologies (TPT), and Professor of Practice at Cornell University’s School of Engineering. He has over 20 years of experience developing investment strategies with the help of machine learning algorithms and supercomputers. Marcos launched TPT after he sold some of his patents to AQR Capital Management, where he was a principal and AQR’s first head of machine learning. TPT is currently engaged by clients with a combined AUM in excess of $1 trillion. Marcos also founded and led Guggenheim Partners’ Quantitative Investment Strategies business, where he managed up to $13 billion in assets, and delivered an audited risk-adjusted return (information ratio) of 2.3.
Marcos has an Erdős #2 according to the American Mathematical Society, and in 2019, he received the ‘Quant of the Year Award’ from The Journal of Portfolio Management.
Thinknum's insights on the recent real-time economic turndown were featured by CNBC, The New York Times, WSJ and Business Insider.
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