Dynamic portfolio management under competing representations
Purpose - To solve the multi-period portfolio management problem under transactions costs. Design/rnethodology/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. indings - 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.
cybernetics portfolio investment optimization techniques programming and algorithm theory