Data mining in finance: From extremes to realism

Boris Kovalerchuk () and Evgenii Vityaev ()
Additional contact information
Boris Kovalerchuk: Central Washington University, Postal: Ellensburg, WA, 98926, USA, http://www.cwu.edu/
Evgenii Vityaev: Russian Academy of Sciences, Postal: 4 Acad. Koptyug avenue, 630090 Novosibirsk, Russia, http://www.math.nsc.ru/

Journal of Financial Transformation, 2004, vol. 11, 81-89

Abstract: This paper describes data mining in finance by discussing financial tasks and specifics of methodologies and techniques in this data mining area. It includes time dependence, data selection, forecast horizon, measures of success, quality of patterns, hypothesis evaluation, problem ID, method profile, attribute-based, and relational methodologies.

Keywords: Data mining; financial services; relational methodologies (search for similar items in EconPapers)
JEL-codes: G21 O33 (search for similar items in EconPapers)
Date: 2004
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ris:jofitr:1366

Access Statistics for this article

Journal of Financial Transformation is currently edited by Prof. Shahin Shojai

More articles in Journal of Financial Transformation from Capco Institute 77 Water Street, 10th Floor, New York NY 10005.
Bibliographic data for series maintained by Prof. Shahin Shojai ( this e-mail address is bad, please contact ).