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Overview
Hear from academics and practitioners on how data science techniques can be used in your investment process. Topics include: using machine learning for stock selection and for risk forecasting, machine learning explainability, predicting returns using textual analysis of news articles, measuring the state of the economy by analyzing business news, using loan applications to predict loan defaults.
Agenda
8:30 AM | REGISTRATION & CHECK-IN
9:00 AM | MACHINE LEARNING FOR STOCK SELECTION
Keywan Rasekhschaffe, Gresham Investment Management
10:00 AM | MACHINE LEARNING FOR RISK FORECASTING
Yuriy Bodjov, CFA, TD Asset Management
11:00 AM | BREAK
11:15 AM | THE INTUITIVE APPEAL OF EXPLAINABLE MACHINES
Solon Barocas, Cornell University, Microsoft Research
12:15 PM | LUNCH
1:15 PM | WHEN WORDS SWEAT: IDENTIFYING SIGNALS FOR LOAN DEFAULT IN THE TEXT OF LOAN APPLICATIONS
Oded Netzer, Columbia Business School
2:15 PM | BREAK
2:30 PM | PREDICTING RETURNS WITH TEXT DATA
Zheng (Tracey) Ke, Harvard University
3:30 PM | THE STRUCTURE OF ECONOMIC NEWS
Bryan Kelly, Ph.D., Yale School of Management, AQR
4:30 PM | NETWORKING & CATERED RECEPTION