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With Joseph Simonian (Founder/CIO, Autonomous Investment).
Monday, April 19, 2021 at 12:30 PM   Absolutely Free   Online

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Modular Machine Learning: The Best of Both Worlds? A Webinar By Joseph Simonian

After reviewing some differences between traditional statistics & data science, we present a modular machine learning framework for model validation which blends the two paradigms. Model validation is set up as a sequence of procedures, in which the output from one procedure serves as the input to another procedure within a single validation framework. An econometric model is used in the first module to classify data in an economically intuitive way. Proceeding modules apply data science techniques to evaluate the predictive characteristics of the model components. We apply the framework to the fundamental law of active management, a well-known formal characterization of portfolio managers alpha generation process. In contrast to standard applications of the law, in which it has been used to evaluate a managers existing active management process, we recast the law within his framework as a means to test investment signals for potential use, individually or collectively, in a managers investment process. To illustrate how this application works, we provide an example using the well-known FamaFrench factors as test signals.

Joseph Simonian is the founder & CIO, Autonomous Investment Technologies & co-editor of the Journal of Financial Data Science. Previously Joe held the roles of Senior Investment Strategist at Acadian Asset Management & Director of Quantitative Research at Natixis Investment Managers, where he led the quantitative research & portfolio strategy for the Portfolio Research & Consulting Group. He was also a member of the investment oversight committee. Prior to working at Natixis, Joseph was the Principal Research Analyst at Global Institutional Solutions. He was also the Vice President of Portfolio Management at J.P. Morgan & PIMCO. Joseph gained his PhD from University of California, Santa Barbara, MA from Columbia University, New York, & BA from University of California, Los Angeles. Joseph is a noted contributor to leading finance journals & is also a prominent speaker at investment events worldwide. He is currently the co-editor of the Journal of Financial Data Science & Advisory Board member for the Journal of Portfolio Management & the Financial Data Professional Institute.

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