Multiperiod Portfolio Selection and Bayesian Dynamic Models
- Friday, September 12 from 3:00 to 4:30 in Room 552; Refreshments 2:30 in Room 502
We present joint work with Petter Kolm on a new theoretical framework for multiperiod optimization with transaction costs which recasts the problem as estimation of a hidden state sequence in a Markov chain. This framework is general enough to encompass the vast majority of the multiperiod portfolio choice and portfolio tracking problems that have thus far appeared in the literature. Constraints are incorporated gracefully with no change to the fundamental theory. The framework leads naturally to practical optimization methods which are shown to converge for a large class of cost functions.
Dr. Gordon Ritter. Buy-side Statistical Arbitrage Alpha Research and Management
Gordon Ritter is an Adjunct Professor at the Courant Institute (NYU), where he teaches graduate-level courses in the Mathematics in Finance program, and at Rutgers where he teaches in the Financial Statistics and Risk Management (FSRM) program. Concurrently with his academic roles he has held several prestigious buy-side positions in the area of statistical arbitrage alpha research and portfolio management. He completed his PhD at Harvard University in mathematical physics, where he published original research in top international journals across several fields including quantum field theory, quantum computation, and abstract algebra. He is a recipient of Harvard's award for excellence in teaching. He also holds an Honors BA from the University of Chicago in Mathematics. LinkedIn: https://www.linkedin.com/profile/view?id=8456749