Conference / Seminar, Fintech Thought Leadership Group, Quantitative Investing, Virtual Events & Programming

Data Science in Finance: Learning from Machine Learning

January 12, 2021 - January 13, 2021

Share Event

Loading Events

Wait! A Note on Registration:

We’ve launched Cvent—our new events platform!

Registration for any event with a start date after Sept. 28 now requires a CFA Institute account.

I don’t have a CFA Institute account

  • No problem! You’ll have the chance to create one prior to registration.

I already have a CFA Institute account

  • Great! Be sure to use your existing credentials at registration.
Cvent Transition Guide

Overview

Co-Hosted by: CFA Society New York &  SQA
In Partnership with FinTech Leadership Group & Quantitative Investing Group

We are thrilled to bring you the fourth installation of our popular annual Data Science conference, this time in an all-virtual format. The theme this year — Learning from Machine Learning – dives into new ML techniques and applications to different areas of investing. We will also explore the issue of ML interpretability.

Registration Options

Single Day Pass

$FREEfor members
  • Nonmembers: $125

2-Day Combo

$FREEfor members
  • Nonmembers: $200

Agenda

Agenda

TUESDAY, JANUARY 12

Alternative Data in Investment Management: Usage, Challenges and Valuation*

Petter Kolm, Director of the Mathematics in Finance Master’s Program, New York University

*This section will not be recorded

The Colour of Finance Words

Diego Garcia, Chair of the Finance Division and Burridge Endowed Chair in Finance at the Leeds School of Business, University of Colorado at Boulder.

Machine Learning in Quantitative Investing

Vladimir Zdorovtsov, Senior Vice President, Director, Global Equity Research, Acadian


Wednesday, JANUARY 13

Fundamental Analysis Via Machine Learning

Haifeng You, Hong Kong University of Science and Technology

The Changing Economics of Knowledge Production

Simona Abis, Columbia Business School

Panel Discussion | Data Science in Finance: Applications and Strategy for the Future

Peg DiOrio, CFA, Head of Head of Quantitative Equity Portfolio Management, Voya Investment Management

Stacie L. Mintz, CFA, Managing Director, Co-Head of the Quantitative Equity team and Portfolio Manager, QMA

Lilian Quah, CFA, Managing Director, Portfolio Manager, Head of Quantitative Research, Epoch Investment Partners

Additional Details

Learning Outcomes

  • Discussion of best AI techniques
  • Assessment of Machine learning in Finance
  • Integration of Data Science in the investment process
  • New applications of machine learning and natural language processing techniques in finance
  • Opportunities and challenges associated with the use of alternative data in investing
  • The potential impact of big data technologies on labor markets and the investment management industry in particular

    About SQA

    The Society of Quantitative Analysts (SQA) is a not-for-profit organization that focuses on education and communication to support members of the quantitative investment community. SQA has hosted educational events in NYC since 1965. The principal mission of SQA is to encourage the dissemination and discussion of leading-edge ideas and innovations, including analytical techniques and technologies for investment research and management. There is more information about SQA and its history on our website: www.sqa-us.org