Distributed Optimisation of a Portfolio's Omega
Parallel Computing, Vol. 36, No. 7, pp. 381-389, 2010
20 Pages Posted: 8 Jul 2008 Last revised: 22 Jul 2011
Date Written: July 7, 2008
We investigate portfolio selection with alternative objective functions in a distributed computing environment. In particular, we optimise a portfolio's 'Omega' which is the ratio of two partial moments of the returns distributions. Since finding optimal portfolios under such performance measures and realistic constraints leads to non-convex problems, we suggest to solve the problem with a heuristic method called Threshold Accepting (TA). TA is a very flexible technique as it requires no simplifications of the problem and allows for a straightforward implementation of all kinds of constraints. Applying this algorithm to actual data, we find that TA is well-adapted to optimisation problems of this type. Furthermore, we show that the computations can easily be distributed which leads to considerable speedups.
Keywords: Optimization heuristics, Threshold Accepting, Portfolio Optimization
JEL Classification: C61, C63, G11
Suggested Citation: Suggested Citation