Data Science in Finance: From Theory to Practice

January 16, 2020 | 8:00 AM - 5:30 PM

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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

9:00 AM | MACHINE LEARNING FOR STOCK SELECTION


10:00 AM | MACHINE LEARNING FOR RISK FORECASTING


11:00 AM | BREAK


11:15 AM | THE INTUITIVE APPEAL OF EXPLAINABLE MACHINES


12:15 PM | LUNCH


1:15 PM |  WHEN WORDS SWEAT: IDENTIFYING SIGNALS FOR LOAN DEFAULT IN THE TEXT OF LOAN APPLICATIONS


2:15 PM | BREAK


2:30 PM | PREDICTING RETURNS WITH TEXT DATA


3:30 PM | THE STRUCTURE OF ECONOMIC NEWS


4:30 PM | NETWORKING & CATERED RECEPTION


Additional Details

Learning Outcomes

  • What are the compensation & talent management trends affecting the industry
  • How large and small companies from different facets of the finance industry are tackling the issue of a tight labor market
  • Expectations of the new generation of employees in the workplace and how companies are addressing them

Features, Benefits, Values

This event will help members and others to understand the current trends in compensation and talent management and how to do what’s best for you or your firm.

Who Should Attend?

CEOs, Chief Operating Officers, Chief Technology Officers, Chief Compliance Officers, Job Seekers, Portfolio Managers, Analysts, Investor Relations