Abstract

Portfolio optimization is going through a revolution with the recent algorithmic advances in conic optimization. By generalizing quadratic optimization, conic optimization allows new ways of modeling and solving a broader class of risk optimization problems efficiently. In this talk, we will give a brief introduction to conic optimization and describe applications in risk modeling, portfolio optimization, transaction cost modeling, value-at-risk minimization. We will go over new techniques for solving hard mixed-integer conic optimization problems. Finally, we will introduce the Bloomberg Portfolio Optimizer built on top of this new technology.

Bio

Alper Atamturk, PhD, is chancellor’s professor of Operations Research at the University of California-Berkeley, director of Berkeley Computational Optimization Lab, and US Department of Defense national security fellow. He is also responsible with research and development of optimization capabilities at Bloomberg LP. His research interests are in the broad area of optimization, including conic optimization, mixed-integer programming, and robust optimization with applications to finance and operations. He serves on the editorial boards of Journal of Risk, Discrete Optimization, Operations Research, and Networks. He regularly serves on the organizing committees of optimization conferences. He served as elected vice chair-integer programming of INFORMS Optimization Society. He received his PhD. from the Georgia Institute of Technology in 1998 with a major in Operations Research and minor in Computer Science.

Please RSVP hugh@QWAFAFEW.org

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