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Big Data Finance 2014

Irene Aldridge, Wall Street and Technology, Optimal Execution in the Age of Big Data, here.

Optimal Execution refers to the science of executing an order in today’s fragmented electronic markets. While many brokers and other market participants still insist on executing orders using intuition and by manually timing the markets, researchers in financial mathematics have developed fine techniques for quick identification of optimal trading conditions. And the industry is taking notice — in the Optimal Execution course I teach for executives from all spectrum of investment lifecycle, nearly 50% of my students routinely come from the largest hedge funds in the U.S. These hedge funds are dissatisfied with the level of sophistication exhibited by their brokers and they are quietly building their own departments with proprietary execution strategies based on the latest cutting-edge research.

Some of this research will be on display at the upcoming Big Data Finance 2014conference to be held at New York University’s Courant Institute for Mathematical Sciences on February 14 from 1 PM to 6 PM.

Big Data Finance 2014, Speakers, here.

Confirmed Speakers: 

Lawrence Glosten, Columbia Business School, “Fleeting Orders”

Lawrence R. Glosten is the S. Sloan Colt Professor of Banking and International Finance at Columbia Business School.  He is also co-director (with Merritt Fox and Ed Greene) of the Program in the Law and Economics of Capital Markets at Columbia Law School and Columbia Business School and is an adjunct faculty member at the Law School.  He has been at Columbia since 1989, before which he taught at the Kellogg Graduate School of Management at Northwestern University, and has held visiting appointments at the University of Chicago and the University of Minnesota.  He has published articles on the microstructure and industrial organization of securities markets; the relationship between venture capitalists and entrepreneurs; evaluating the performance of portfolio managers and asset pricing.  His work on electronic exchanges in the Journal of Finance won a Smith Breeden Distinguished Paper Prize.  He has served as an editor of the Review of Financial Studies, associate editor of the Journal of Finance and serves on several other editorial boards.  He has been a consultant for the New York Stock Exchange, Justice Department, and SEC and has served on the NASDAQ Economic Advisory Board.  He received his AB from Occidental College (1973) and his Ph.D. in managerial economics from Northwestern University (1980).

Jim Angel, Wharton School of Business and McDonough School of Business, Georgetown University

James J. Angel is a visiting associate professor at The Wharton School of the University of Pennsylvania where he teaches Capital Markets.  He will return to his permanent position at Georgetown University in 2014.  Jim serves on the board of directors of the Direct Edge Stock Exchange and is a former Visiting Academic Fellow at the NASD.  He has testified five times before Congress, and is a co-inventor of 11 patents on financial technology.  He has also been quoted numerous times in the media and appeared on CNN, CNBC, Jim Lehrer News Hour and the Jay Leno Show, among others.  Jim’s hobby is to visit stock exchanges ( — he has visited over 70 of them around the world –)  and to visit trading desks.  Jim earned his B.S. in engineering from Caltech, his MBA from Harvard Business School, and his Ph.D. from U.C. Berkeley.  You can follow him on twitter at #GUFinProf.

Steve Shreve, Carnegie Mellon University, “Brownian Motion Limit Model of a Limit-Order Book”

Steven Shreve is the Orion Hoch and University Professor of Mathematics at Carnegie Mellon University, where he co-founded the CMU Master’s degree in Computational Finance, now in its 19th year, with campuses in New York and Pittsburgh.  Shreve’s book “Stochastic Calculus for Finance” won the 2004 Wilmott award for the “Best New Book in Quantitative Finance.”  Shreve is co-author of the books “Brownian Motion and Stochastic Calculus” and “Methods in Mathematical Finance,” advisory editor of “Finance and Stochastics,” and past President of the Bachelier Finance Society.  He has published over forty articles in scientific journals on stochastic calculus, stochastic control, and the application of these subjects to finance, including the effect of transaction costs and unknown volatility on option prices, hedging exotic options, and models of credit risk.

Marco Avellaneda, Courant Institute, New York University, “Optimal Execution in the Presence of Limited Liquidity”

Jacob Loveless, Lucera HQ

Dongsheng Lu, Bank of America Mellon

Elana Marguiles, Chief Reporter, Hedge Fund Managers Weekly, Panel Moderator

Marcin Osiecki, JP Morgan

Stefan Karpinski, MIT, “Julia, The New Computing Language: Fast Performance, Distributed Computing, and Multiple Dispatch”

Stefan Karpinski is one of the co-creators and core developers of the Julia language.  He is an applied mathematician and data scientist by trade.  Stefan is currently a research scientist at MIT, focused on advancing Julia’s design, performance and scalability.

Sasha Stoikov, Cornell University

Irene Aldridge, ABLE Alpha Trading, LTD., “The Cost of Latency”

Irene Aldridge is a Managing Partner of ABLE Alpha Trading, a quantitative investment advisory and consulting firm.  She is the author of “High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems,” translated into Chinese and now in its second edition.  Aldridge’s latest research on Flash Crash predictability is forthcoming in the Journal of Portfolio Management in the Summer of 2014.

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