Useful Pattern Mining on Time Series: Applications in the Stock Market

Nikitas Goumatianos, Ioannis T Christou, Peter Lindgren

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5 Citationer (Scopus)

Abstract

We present the architecture of a “useful pattern” mining system that is capable of detecting thousands of different candlestick sequence patterns at the tick or any higher granularity levels. The system architecture is highly distributed and performs most of its highly compute-intensive aggregation calculations as complex but efficient distributed SQL queries on the relational databases that store the time-series. We present initial results from mining all frequent candlestick sequences with the characteristic property that when they occur then, with an average at least 60% probability, they signal a 2% or higher increase (or, alternatively, decrease) in a chosen property of the stock (e.g. close-value) within a given time-window (e.g. 5 days). Initial results from a first prototype implementation of the architecture show that after training on a large set of stocks, the system is capable of finding a significant number of candlestick sequences whose output signals (measured against an unseen set of stocks) have predictive accuracy which varies between 60% and 95% depended on the type of pattern.
OriginalsprogEngelsk
TitelProceedings of the 2nd International Conference on Pattern Recognition Applications and Methods (ICPRAM 2013)
Antal sider4
Vol/bind20
ForlagInternational Conference on Pattern Recognition Applications and Methods
Publikationsdato2013
Sider608-612
ISBN (Trykt)978-989856541-9
StatusUdgivet - 2013
BegivenhedICPRAM 2013 - Barcelona, Spanien
Varighed: 15 feb. 201318 feb. 2013

Konference

KonferenceICPRAM 2013
Land/OmrådeSpanien
ByBarcelona
Periode15/02/201318/02/2013

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