WatRISQ Seminar called "Multi-period Mean Variance Asset Allocation: Is it Bad to Win the Lottery?"
Presenter: Prof. Peter Forsyth
Speaker: Peter Forsyth, Professor, David R. Cheriton School of Computer Science University of Waterloo, Ontario
We present semi-self-financing mean-variance (MV) dynamic asset allocation strategies which are superior to self-financing MV portfolio strategies. Our strategies are built upon a Hamilton-Jacobi-Bellman (HJB) equation approach for the solution of the portfolio allocation problem.
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, and realistic portfolio constraints.
MV strategies are often criticized for penalizing the upside as well as the downside. However, 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. We show that, for long term investors, the use of dynamic MV strategies can achieve the same expected value with a much smaller standard deviation compared to a constant proportions strategy.
To find out more, contact the Waterloo Research Institute in Insurance, Securities and Quantitative Finance, University of Waterloo, MC 6007C -(519) 888-4567 ext. 31043 email@example.com
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