By the same authors

Application of correlation memory matrices in high frequency asset allocation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Publication details

Title of host publicationFIFTH INTERNATIONAL CONFERENCE ON ARTIFICIAL NEURAL NETWORKS
DatePublished - 1997
Pages167-172
Number of pages6
PublisherINST ELECTRICAL ENGINEERS INSPEC INC
Place of PublicationEDISON
Original languageEnglish
ISBN (Print)0-85296-690-3

Abstract

Tactical asset allocation is one of the most important aspects of modern financial management. This paper looks at a forecasting architecture that can be used for performing asset allocation with higher frequency thus allowing better response to market changes and hence better adherence to customer's risk-reward profiles. The architecture is based on a variant of correlation memory matrix and utilises Bayesian probabilities of recalled classes to perform better forecasts.

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