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SQA/CFA Society NY Joint Conference "Data Science in Finance, The Final Frontier?"
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 Export to Your Calendar 1/18/2018
When: Thursday, January 18, 2018


Online registration is available until: 1/18/2018
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Time: 8:30 am – 5:30 pm

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

*Enter from 45th St.

 

Description:

In recent years the topics of Data Science, Artificial Intelligence, Machine Learning & Big Data have become increasingly popular. This growth has been fueled by the collection & availability of new data; continually increasing processing power & storage and the open source movement making tools more widely available. As a result, we have already witnessed profound changes to how we work, rest and play. And this trend will only increase ...But how has the world of finance been impacted and investment managers in particular?Join us to explore what Data Science means for finance professionals.

 

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.  

 

Learning outcomes:

-          Gain an understanding of various big data techniques;

-          Learn new algorithms for investment analysis;

-          Review how data science is applied in various industries.

 

Agenda

 8:30 – 9:00 a.m.     Registration Breakfast
 9:00 – 10:00 a.m.        Vasant Dhar, New York University - Topic TBA
 10:00 – 11:00 a.m.             Robert Schapire, Microsoft - “The Contextual Bandits Problem: Techniques for Learning to Make High-Reward Decisions”
 11:00 – 11:15 a.m.   Coffee Break
 11:15 – 12:15 p.m.   Bryan Kelly, University of Chicago - “Text as Data”
 12:15 – 1:15 p.m.   Lunch
 1:15 - 2:15 p.m.   Paul Gao, University of Notre Dame - “Search Data and Finance”
 2:15 - 3:15 p.m.  Ronnie Sadka, Boston College - “Media and Its Interaction with Financial Markets”
 3:15 - 3:30 p.m.  Coffee Break
 3:30 – 4:30 p.m.   Claudia Perlich, Dstillery – topic tba
 4:30 – 5:30 p.m.   Cocktails/Networking

 

 

Robert Schapire, Microsoft - “The Contextual Bandits Problem: Techniques for Learning to Make High-Reward Decisions”

 

Robert Schapire is a Principal Researcher at Microsoft Research in New York City.  He received his PhD from MIT in 1991.  After a short post-doc at Harvard, he joined the technical staff at AT&T Labs (formerly AT&T Bell Laboratories) in 1991.  In 2002, he became a Professor of Computer Science at Princeton University.  He joined Microsoft Research in 2014.  His awards include the 1991 ACM Doctoral Dissertation Award, the 2003 Gödel Prize, and the 2004 Kanelakkis Theory and Practice Award (both of the last two with Yoav Freund).  He is a fellow of the AAAI, and a member of both the National Academy of Engineering and the National Academy of Sciences.  His main research interest is in theoretical and applied machine learning, with particular focus on boosting, online learning, game theory, and maximum entropy.

 

 

Bryan Kelly, University of Chicago - “Text as Data”

 

Bryan Kelly is Professor of Finance at the University of Chicago Booth School of Business, a Research Fellow at the National Bureau of Economic Research, visiting professor at the Yale School of Management, and a consultant at AQR Capital Management. Professor Kelly’s primary research fields are asset pricing and financial econometrics. He is interested in volatility, correlation, and tail risk in financial markets, banking sector systemic risk, financial intermediation, financial networks, and statistical methods for high dimensional systems. His papers have been published in the American Economic Review, the Quarterly Journal of Economics, the Journal of Finance, the Journal of Financial Economics, and the Review of Financial Studies, among others. He is an associate editor at the Journal of Finance, the Journal of Business and Economic Statistics and the Journal of Financial Econometrics. Kelly is a two time finalist and one time winner of the AQR Insight Award, and is a winner of various other awards and research grants including the Fama/DFA Prize for best asset pricing paper in the Journal of Financial Economics, the Jack Treynor Prize, the Roger F. Murray Award, and the JP Morgan Award for Best Paper on Financial Institutions and Markets.

 

Before joining the University of Chicago, Kelly earned a bachelor’s degree in economics from the University of Chicago, a master’s degree in economics from University of California San Diego, and a PhD in finance from the New York University’s Stern School of Business. Kelly worked in investment banking at Morgan Stanley prior to pursuing his PhD.

 

 

Paul Gao, University of Notre Dame - “Search Data and Finance”

 

Paul Gao first joined the University of Notre Dame in 2007, where he is currently the Viola D. Hank Associate Professor of Finance. He was an associate professor of finance at the Hong Kong University of Science and Technology (HKUST) Business School, and a visiting senior economist at the Shanghai Stock Exchange (SHSE). He has published in the Journal of Finance, the Review of Financial Studies, and the Journal of Financial Economics. He is the past winner of the prestigious Fama-DFA Prize, Cowen Memorial Prize, CQA Research Award, and Q-Group Research Award. He serves as the associate editors for the Pacific Basin Finance Journal, and the Financial Management. He earned his doctoral degree in Financial Economics from Kellogg School of Management, Northwestern University in 2007.

 

 

Ronnie Sadka, Boston college - “Media and It's Interaction with Financial Markets”

 

Professor Ronnie Sadka Senior Associate Dean and chairperson of the finance department at the Carroll School of Management, Boston College. His research focuses on the liquidity in financial markets. More recently, he has been developing big-data driven investment applications. Sadka is a frequent speaker at academic and practitioner conferences; his work has appeared in various outlets including Journal of Finance, Journal of Financial Economics, Journal of Accounting Research, Journal of Accounting and Economics, Journal of Financial and Quantitative Analysis, and Financial Analysts Journal, and has been covered by New York Times, Wall Street Journal, and CNBC.

 

Prior academic experience includes teaching at the University of Chicago (Booth), New York University (Stern), Northwestern University (Kellogg), and the University of Washington (Foster). Industry experience includes Goldman Sachs Asset Management and Lehman Brothers (quantitative strategies). Sadka recently served on the economic advisory board of NASDAQ OMX. Professor Sadka earned a B.Sc. (Magna Cum Laude) in industrial engineering and a M.Sc. (Summa Cum Laude) in operations research, both from Tel-Aviv University. He received a Ph.D. in finance from Northwestern University (Kellogg).

 

 

Claudia Perlich, Dstillery – topic tba

 

Claudia Perlich leads the machine learning efforts that power Dstillery’s digital intelligence for marketers and media companies.  With more than 50 published scientific articles, she is a widely acclaimed expert on big data and machine learning applications, and an active speaker at data science and marketing conferences around the world.
 
Claudia is the past winner of the Advertising Research Foundation’s (ARF) Grand Innovation Award and has been selected for Crain’s New York’s 40 Under 40 list, Wired Magazine’s Smart List, and Fast Company’s 100 Most Creative People.
 
Claudia holds multiple patents in machine learning.  She has won many data mining competitions and awards at Knowledge Discovery and Data Mining (KDD) conferences, and served as the organization’s General Chair in 2014.
 
Prior to joining Dstillery in 2010, Claudia worked at IBM’s Watson Research Center, focusing on data analytics and machine learning.  She holds a PhD in Information Systems from New York University (where she continues to teach at the Stern School of Business), and an MA in Computer Science from the University of Colorado.

 

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

 

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 10,000 members, CFA Society New York is the largest of more than 142 societies worldwide that comprise CFA Institute. You can find more information about the organization at:  www.cfany.org

 

 

SQA/CFA Society NY Joint Conference "Data Science in Finance, the Final Frontier?" has gone mobile!

We're excited to announce that we have a brand new mobile guide for you! Get the guide to access the most up-to-date information about our event, including schedule, talk summaries, speaker bios, map, and more.

Get our guide here: http://guidebook.com/g/sqacfany2018

Android and iOS users:

1.  Tap the "Download" button to download the free Guidebook app

2.   Open Guidebook and you can find our SQA/CFA Society NY Joint Conference "Data Science in Finance, the Final Frontier?" guide

See you there!

 

 

SQA Member - $525

Non-member - $695
Student/Transitional Member - $295

Non-Member (Affiliated) - $595 Please contact your organization for the discount code

 

Early Bird Discount - Receive $100 off!

 

 

Click Here to become a member today! 


 

 

Please contact the office at admin@sqa-us.org or 518-694-3157 if you would like to register over the phone

 

 

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