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Soft Computing

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18.09.2017 | Methodologies and Application

Mining stock category association on Tehran stock market

verfasst von: Zahra Hoseyni Masum

Erschienen in: Soft Computing | Ausgabe 4/2019

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Abstract

Following the recent efforts made to achieve a predictable capital market, this study attempted to explore the interlocking relationships between the stock returns of companies listed on Tehran stock exchange (TSE). For that purpose, data concerning 36 industry classes between 2000 and 2013 were examined through clustering and association rule. Preparation and initial refining of data suggested that only 25 out of 36 industries met the requirement for 13-year membership at TSE. Finally, a total of 249,061 records were evaluated, and the results were presented in the form of several rules and recommendations for investors. The results suggested that there were no two-item rules (rules with one antecedent) within industries. The best rules entailed three and four items with a lift of more than two, confidence more than 81% and support more than 1%.

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Titel: Mining stock category association on Tehran stock market
verfasst von: Zahra Hoseyni Masum
Publikationsdatum: 18.09.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 4/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-017-2835-9

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