Committee Meeting, Free for Members, Group Meeting, Interest Group, Interest Group Meetings, Quantitative Investing, Virtual Events & Programming

Quantitative Investing Group Meeting

Friday, July 9 | 12:00 PM - 1:30 PM

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Cvent Transition Guide

Overview

Investing is historically an early adopter of new algorithms and technology.  The utility of a new idea is straightforwardly measured in money out over money in. Machine Learning and large-scale computing of unstructured, novel data provides a new set of methods that were developed first by internet companies. These methods primarily provide an informational advantage in an inefficient market where securities are selected based on their underlying intrinsic value.  In this talk I describe the underlying methods, provide examples of success using these methods, and I present a roadmap for the impact these methods will have on markets and investing.

Quantitative Investing Group

Guest Speaker

Dr. Michael Recce, Alpha ROC 

Michael Recce was the first Chief Data Scientist at Neuberger Berman, GIC, the Singapore Sovereign Wealth Fund, and Point72 Asset Management.   Before taking these roles in the finance industry, he was head of engineering and the head of modeling and optimization at Quantcast, where he led a team of machine learning and computer science experts in the design of high volume, targeted, real-time bidding for internet advertising.  Earlier in his career, he was Chief Scientist for Fortent, and Searchspace that provided market leading transaction monitoring, risk assessment, and fraud detection systems for financial institutions.

Dr. Recce was also a product engineering manager at Intel Corporation, where he led the development of new memory products for the company.  Dr. Recce has published over 60 peer reviewed papers, and holds eleven patents, including one for research of a behavioral biometric called dynamic grip recognition, and is a recipient of the Thomas A. Edison Award [2005]. Dr. Recce has been a tenured faculty member at University College, London (UCL), and a professor of information systems at New Jersey Institute of Technology. He received his bachelor’s degree in Physics from the University of California Santa Cruz and his doctorate in Neuroscience from UCL.