Department of Business Development and Technology

An algorithmic framework for frequent intraday pattern recognition and exploitation in forex market

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  • Nikitas Goumatianos, Athens Information Technology-AIT, Aalborg University
  • ,
  • Ioannis T. Christou, Athens Information Technology-AIT
  • ,
  • Peter Lindgren
  • Ramjee Prasad

We present a knowledge discovery-based framework that is capable of discovering, analyzing and exploiting new intraday price patterns in forex markets, beyond the well-known chart formations of technical analysis. We present a novel pattern recognition algorithm for Pattern Matching, that we successfully used to construct more than 16,000 new intraday price patterns. After processing and analysis, we extracted 3518 chart formations that are capable of predicting the short-term direction of prices. In our experiments, we used forex time series from 8 paired-currencies in various time frames. The system computes the probabilities of events such as “within next 5 periods, price will increase more than 20 pips”. Results show that the system is capable of finding patterns whose output signals (tested on unseen data) have predictive accuracy which varies between 60 and 85% depending on the type of pattern. We test the usefulness of the discovered patterns, via implementation of an expert system using a straightforward strategy based on the direction and the accuracy of the pattern predictions. We compare our method against three standard trading techniques plus a “random trader,” and we also test against the results presented in two recently published studies. Our framework performs very well against all systems we directly compare , and also, against all other published results.

Original languageEnglish
JournalKnowledge and Information Systems
Volume53
Issue3
Pages (from-to)767-804
Number of pages38
ISSN0219-1377
DOIs
Publication statusPublished - 1 Dec 2017

    Research areas

  • Data mining, Forex, Hidden intraday patterns, Pattern recognition, Template grid method

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