John Tsitsiklis
John N. Tsitsiklis was born in Thessaloniki, Greece, in 1958. He received the B.S. degree in Mathematics (1980), and the B.S. (1980), M.S. (1981) and Ph.D. (1984) degrees in Electrical Engineering, all from the Massachusetts Institute of Technology, Cambridge, Massachusetts, U.S.A.
During the academic year 1983-84, he was an acting assistant professor of Electrical Engineering at Stanford University, Stanford, California. Since 1984, he has been with the department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology, where he is currently a Clarence J Lobel Professor of Electrical Engineering. He has served as acting co-director of the MIT Laboratory for Information and Decision Systems (Spring 1996 and 1997), and as a co-director of the Operations Research Center (July 2002-December 2005).
He has been a visitor with the Dept. of EECS at the University of California at Berkeley, and the Institute for Computer Science in Iraklion, Greece. His research interests are in the fields of systems, optimization, control, and operations research. He has coauthored more than 100 journal papers in these areas. He is also named as coinventor in 5 awarded U.S. patents.
He is a coauthor of Parallel and Distributed Computation: Numerical Methods (1989, with D. Bertsekas), Neuro-Dynamic Programming (1996, with D. Bertsekas), Introduction to Linear Optimization (1997, with D. Bertsimas), and Introduction to Probability (2002, with D. Bertsekas).
He has been a recipient of an IBM Faculty Development Award (1983), an NSF Presidential Young Investigator Award (1986), an Outstanding Paper Award by the IEEE Control Systems Society (1986), the M.I.T. Edgerton Faculty Achievement Award (1989), the Bodossaki Foundation Prize (1995), the INFORMS Computer Science Technical Section prize (1997), and is a Fellow of the IEEE (1999). In 2007, he was elected to the National Academy of Engineering.
He was a plenary speaker at the 1992 IEEE Conference on Decision and Control and at the MTNS'2000. He has been an associate editor of the IEEE Transactions on Automatic Control, Automatica, Applied Mathematics Letters, and Mathematics of Operations Research. He is currently a member of the editorial board for the Springer-Verlag "Lecture Notes in Control and Information Sciences" series. Finally, he is a member of the National Council on Research and Technology in Greece.
Articles by this Author
Regression Methods for Pricing Complex American-Style Options
- By John Tsitsiklis
- Published 10/11/2007
- Price modeling
- Unrated
Published in:
Publication year: 2000
Co-author 1: Benjamin van Roy
We introduce and analyze a simulation-based, approximate dynamic programming method for pricing complex American-style options, with a possibly high-dimensional underlying state space. We work within a finitely parameterized family of approximate value functions, and introduce a variant of value iteration, adapted to this parametric setting. We also introduce a related method which uses a single (parameterized) value function, which is a function of the time-state pair, as opposed to using a separate (independently parameterized) value function for each time. Our methods involve the evaluation of value functions at a finite set, consisting of "representative" elements of the state space. We show that with an arbitrary choice of this set, the approximation error can grow exponentially with the time horizon (time to expiration). On the other hand, if representative states are chosen by simulating the state process using the underlying risk-neutral probability distribution, then the approximation error remains bounded.
