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With Peter Decrem (Dir. Rates Trading, Citi), Darren Vengroff (SVP, Two-Sigma), Amanda Stent (Researcher, Bloomberg), Rama Cont (Prof. Mathematical Finance, Oxford), Kay Giesecke (Prof. Engg, Stanford), Simona Abis (Prof., Columbia Business School), Yange Leng (Research Assistant, MIT).
Friday, May 17, 2019 at 08:15 AM   $40
Columbia University, 2920 Broadway, Lerner Hall
 
     
 
 
              

      
 
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The Data Science Institute (DSI) at Columbia University & Bloomberg are pleased to announce a workshop on "Machine Learning in Finance". The workshop will be held at Columbia University under the auspices of the Financial & Business Analytics Center, one of the constituent centers in the DSI, & the Center for Financial Engineering.
Boxed lunches will be provided. There will also be regular coffee breaks throughout the day & a wine & cheese reception after the event.


The Center for Financial Engineering & the Financial Analytics Center at Columbia University
Organizer of Machine Learning in Finance Workshop 2019





TheCenter for Financial Engineeringis an interdisciplinary research center established in 2007 to encourage research on financial engineering & mathematical modeling in finance. It aims at fostering research collaboration among Columbia faculty, graduate students & affiliates, facilitating their contacts with financial institutions & corporations & enhancing the visibility of Columbia as a center for research & innovation in financial engineering.
The Center's research activities deal with the pricing & hedging of derivative securities, the statistical modeling of financial markets, computational methods in finance, risk management, asset allocation & portfolio optimization.
TheFinancial Analytics Centeris one of the key centers at the Data Sciene Institute at Columbia University. It brings together expertise in finance theory, machine learning, statistics, signal processing, operations, & natural language processing, & supports collaborations with an appropriately trained student body as well as with the financial industry.






 
 
 
 
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