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ISRN Artificial Intelligence
Volume 2014 (2014), Article ID 451849, 10 pages
Research Article

Study on the Effectiveness of the Investment Strategy Based on a Classifier with Rules Adapted by Machine Learning

West Pomeranian University of Technology, Żołnierska 49, 71-210 Szczecin, Poland

Received 29 September 2013; Accepted 12 December 2013; Published 3 February 2014

Academic Editors: J. Bajo and K. W. Chau

Copyright © 2014 A. Wiliński et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper examines two transactional strategies based on the classifier which opens positions using some rules and closes them using different rules. A rule set contains time-varying parameters that when matched allow making an investment decision. Researches contain the study of variability of these parameters and the relationship between learning period and testing (using the learned parameters). The strategies are evaluated based on the time series of cumulative profit achieved in the test periods. The study was conducted on the most popular currency pair EURUSD (Euro-Dollar) sampled with interval of 1 hour. An important contribution to the theory of algotrading resulting from presented research is specification of the parameter space (quite large, consisting of 11 parameters) that achieves very good results using cross validation.