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2nd Annual SQA/CFA Society NY Joint Conference
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 Export to Your Calendar 1/24/2019
When: Thursday, January 24, 2019

Online registration is available until: 1/24/2019
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Title: 2nd Annual SQA/CFA Society NY Joint Conference

         "Data Science in Finance: looking beyond the hype”

Date: January 24th, 2019

Time: 8:30 am – 5:30 pm

Venue: CFA Society New York, 1540 Broadway, New York, NY


*First 100 people to register get $170 discount*



Speakers (click for abstracts & bios)

- Sanjeev Arora, Princeton University - "What is Machine Learning and Deep Learning?"

- Peter Cotton, JP Morgan and Stanford University – “Open Source Random Variables: Building a Prediction Web.”

- Ingrid Daubechies, Duke University – “Mathematicians helping art conservators and art historians.”

- Bryan Kelly, Yale University and AQR - “Can Machines Learn Finance?”

- Ken Perry, Consultant in Risk and Quantamental Investing, CRO, formerly of Och Ziff - "Challenge for Finance: AI Interpretability."

- Nick Polson, the University of Chicago - "Deep Learning in Finance."*


(* ) To be confirmed.




Data Science is blossoming in the financial industry and literature. More and more financial firms are introducing machine learning systems to forecast markets and trade. Academics are astounded by “unprecedented out-of-sample return prediction” ability of ML and are setting а “new standard for accuracy in measuring risk premia.”[1]  They find that “in designing and pricing securities, constructing portfolios, and risk management… deep learning can detect and exploit interactions in the data that are, at least currently, invisible to any existing financial economic theory.”[2]  At the same time, “rapid empirical success in this field currently outstrips mathematical understanding.”[3]


Join us to learn from leading academics and practitioners about Data Science applications in finance and to understand what’s behind these techniques and why they work so well.


Who would be interested in this event:

Analysts, Portfolio Managers and other practitioners interested in how machine learning, artificial intelligence, and other data science techniques can be used in financial and other sectors.  


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:


About CFA Society New York

CFA Society New York (formerly NYSSA) has been a leading forum for the investment community since 1937. Its mission is to serve the needs of investment professionals and to educate the investing public. With over 11,000 members, CFA Society New York is the largest of more than 152 societies worldwide that comprise CFA Institute. You can find more information about the organization at:

[1] Shihao Gu, Bryan Kelly and Dacheng Xiu ”Empirical Asset Pricing via Machine Learning.” Chicago Booth Research Paper No. 18-04


[2] J. B. Heaton, N. G. Polson and J. H. Witte “Deep Learning in Finance.” arXiv:1602.06561v3 [cs.LG] 14 Jan 2018


[3] Sanjeev Arora “Mathematics of Machine Learning: An introduction.”


*First 100 people to register get $170 discount*

Early Bird Pricing 

SQA Member - $425

Non-Member - $525
Student/Transitional Member - $250

Non-Member (Affiliated) - $475


Regular Pricing


SQA Member - $595

Non-Member - $695

Student/Transitional Member - $250

Non-Member (Affiliated) - $645



Click Here to become a member today! 



Please contact the office at or 518-694-3157 if you would like to register over the phone



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