New York University will host the second annual Algorithmic Trading Conference on Friday, February 5, 8:30 a.m.—6 p.m., at NYU s Jack H. Skirball Center for the Performing Arts (566 LaGuardia Place [at Washington Square South]).

Algorithmic Trading

New York University will host the second annual Algorithmic Trading Conference on Friday, February 5, 8:30 a.m.—6 p.m., at NYU’s Jack H. Skirball Center for the Performing Arts (566 LaGuardia Place [at Washington Square South]).

General registration fee is $900. Discounts apply to students and academics. For more information, a schedule of sessions, and to register, go to: http://math.nyu.edu/~mathfcon/index.php/upcoming-events/feb-5-2010.

For questions or inquiries, please e-mail mathfcon@cims.nyu.edu or call 212.998.4855. Reporters interested in attending the workshop must RSVP to James Devitt, NYU’s Office of Public Affairs, at 212.998.6808 or james.devitt@nyu.edu. The event is organized by the Mathematics in Finance Masters Program at NYU’s Courant Institute of Mathematical Sciences and the Heimdall Group, LLC.

Speakers will include: Ananth Madhavan, managing director at BlackRock, Inc; Terrence Hendershott, an associate professor at the University of California, Berkeley’s Haas School of Business; Joel Hasbrouck, Kenneth G. Langone Professor of Business and professor of finance at NYU’s Stern School of Business, and Ronnie Sadka, an associate professor at Boston College’s Carroll School of Management.

Algorithmic trading employs computer programs to enter trade orders, with algorithms used to decide the timing, price, and quantity of the order. This practice is widely used by hedge funds, pension funds, and mutual funds. But in a highly volatile financial environment, some have raised questions on the reliability of algorithmic trading and emphasized the importance of human interpretation of markets.

Topics of the conference include: dynamic portfolio management; anti-gaming algorithms; crossing network and dark pool optimization; construction of price impact models using public and non-public data; execution risk analytics, including bias-free covariance matrices and factor models; integration of cost aware portfolio construction and optimal execution; post-trade analytics and quantitative comparison of execution strategies; intraday data patterns, machine-readable news and trading strategies; and, latency.


EDITOR’S NOTE:
New York University’s Courant Institute of Mathematical Sciences is a leading center for research and education. Established under the leadership of Richard Courant in 1935, the Courant Institute has contributed to U.S. and international science and engineering by promoting an integrated view of mathematics and computer science. The Institute is engaged in broad research activities, applying these disciplines to problems in biology, chemistry, physics, economics, and atmosphere-ocean science. The Courant Institute has played a central role in the development of applied mathematics, analysis, and computer science, and is comprised of a faculty which has received numerous national and international awards in recognition of their extraordinary research accomplishments. For more information please visit www.cims.nyu.edu.

Press Contact

James Devitt
James Devitt
(212) 998-6808