Forecasting Changes in Stock Prices on the Basis of Patterns Identified with the Use of Data Classification Methods

Szanduła Jacek ()
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Szanduła Jacek: Ph.D. Wroclaw University of Economics Department of Economic Forecasts and Analyses Komandorska 118/120, Wrocław, Poland

Folia Oeconomica Stetinensia, 2014, vol. 14, issue 1, 7-21

Abstract: The paper develops the concept of harnessing data classification methods to recognize patterns in stock prices. The author defines a formation as a pattern vector describing the financial instrument. Elements of such a vector can be related to the stock price as well as sales volume and other characteristics of the financial instrument. The study uses data concerning selected companies listed on the stock exchange in New York. It takes into account a number of variables that describe the behavior of prices and volume, both in the short and long term. Partitioning around medoids method has been used for data classification (for pattern recognition). An evaluation of the possibility of using certain formations for practical purposes has also been presented.

Keywords: data classification; cluster analysis; partitioning around medoids; technical analysis; price patterns (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:foeste:v:14:y:2014:i:1:p:15:n:1

DOI: 10.2478/foli-2014-0101

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