Dynamic portfolio management under competing representations

Abstract

Purpose

To solve the multi‐period portfolio management problem under transactions costs.

Design/methodology/approach

We apply a recently designed super genetic hybrid algorithm (SuperGHA) – an integrated optimisation system for simultaneous parametric search and non‐linear optimisation – to a recursive portfolio management decision support system (SHAREX). The parametric search machine is implemented as a genetic superstructure, producing tentative parameter vectors that control the ultimate optimisation process.

Findings

SHAREX seems to outperform the buy and hold‐strategy on the Finnish stock market. The potential of a technical portfolio system is best exploitable under favorable market conditions.

Originality/value

A number of robust engines for matrix algebra, mathematical programming and numerical calculus have been integrated with SuperGHA. The engines expand its scope as a general‐purpose algorithm for mathematical programming.

Citation

Östermark, R. (2005), "Dynamic portfolio management under competing representations", Kybernetes, Vol. 34 No. 9/10, pp. 1517-1550. https://doi.org/10.1108/03684920510614795