Logic mining for financial data

Authors:
G. Felici;M. A. Galante;L. Torosantucci
Affiliations:
Istituto di Analisi dei Sistemi ed Informatica del CNR, Roma, Italy;Istituto di Analisi dei Sistemi ed Informatica del CNR, Roma, Italy;Banca Nazionale del Lavoro
Venue:
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
Year:
2006

Citing 5
Cited 0

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Abstract

In this paper we consider a new strategy for supporting timing decisions in stock markets. The approach uses the logic data miner Lsquare, based on logic optimisation techniques. We adopt a novel concept of good session, based on the best return expected within a given time horizon. Such definition links indirectly the buying decision with the selling decision and make it possible to exploit particular features of stock time series. The method is translated into an investment strategy and then it is compared with the standard buy & hold strategy.