Distributed Optimisation of a Portfolio's Omega

Manfred Gilli () and Enrico Schumann

No 08-17, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: 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; Distributed Computing (search for similar items in EconPapers)
JEL-codes: C61 C63 G11 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2008-07
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp0817

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