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Department of Systems Engineering and Engineering Management
The Chinese University of Hong Kong

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Title: Better than pre-commitment mean-variance portfolio allocation strategies: a semi-self-financing Hamilton-Jacobi-Bellman equation approach

Speaker: Prof. Peter Forsyth,
Cheriton School of Computer Science, University of Waterloo
Date: July 8, 2014 (Tuesday)

Time: 4:00 PM to 5:00 PM

Venue: Room 513
William M.W. Mong Engineering Building (ERB)
(Engineering Building Complex Phase 2)
The Chinese University of Hong Kong.

Short Biography of the speaker:
After graduating in 1979, Peter Forsyth was a Senior Simulation Scientist at the Computer Modelling Group (CMG) in Calgary, where he developed petroleum reservoir simulation software. After leaving CMG, Peter was the founding President of software startup Dynamic Reservoir Systems (DRS), also in Calgary.

In 1987, Peter joined the University of Waterloo, where he is now a Professor in the Cheriton School of Computer Science. Peter's current research focuses on Computational Finance, with particular focus on numerical methods for Hamilton Jacobi Bellman partial differential equations. He is a member of the Editorial Board of Applied Mathematical Finance and the Journal of Computational Finance. He was the Editor-in-chief of JCF for the period 2008-2013.

Peter is currently a director of Aquanty, a software startup specializing in integrated modelling of three dimensional surface/subsurface water flows. Aquanty specializes in simulating the impact of industrial activity and climate change on water resources.

Abstract:
We present semi-self-financing mean-variance (MV) strategies which are superior to self-financing strategies for the pre-commitment optimal MV portfolio allocation problem. Our strategies are built upon a Hamilton-Jacobi-Bellman (HJB) equation approach for the solution of the portfolio allocation problem, and differ from self-financing strategies primarily in situations where the wealth of the portfolio exceeds a certain threshold. In such a situation, we extend the idea of the semi-self-financing approach originally developed in (Cui et al), Mathematical Finance 22 (2012) 346-378.

Under an HJB framework, our strategies have a simple and intuitive derivation, and can be readily employed in a very general setting, namely continuous or discrete re-balancing, jump-diffusions with finite activity, and realistic portfolio constraints. Moreover, under our strategies, the MV portfolio optimization problem can be shown to be equivalent to maximizing the expectation of a well-behaved utility function of the portfolio wealth.

Numerical results confirming the superiority of the efficient frontiers produced by our strategies are presented.

Everyone is invited to attend the talk.

The talk will be hosted by:
Prof. Duan Li,
Department of Systems Engineering and Engineering Management,
The Chinese University of Hong Kong,
E-mail: dli@se.cuhk.edu.hk
Telephone Number: (852) 3943-8323

For general enquiries, please contact the student coordinator:
Andy Chung,
Department of Systems Engineering and Engineering Management,
The Chinese University of Hong Kong,
E-mail: oychung@se.cuhk.edu.hk

SEEM-5202 Website: http://seminar.se.cuhk.edu.hk
Email: seem5202@se.cuhk.edu.hk