DATA MINING AND APPLICATION OF IT TO CAPITAL MARKETS

Nowadays with the development of technology importance given to knowledge increases gradually. Data mining enables to form forecasts and models regarding future by making use of past data. Any method which helps to discover data can be used as a data mining method. Enterprises gain important competitive advantage by data mining methods. Data mining is used in different fields. In finance field it is a specially used in financial performance applications, guessing the enterprise bankruptcies and failures, determining transaction manipulation, determining financial risk management, determining customer profile and depth management. It can be costly, risky and time consuming for enterprises to gain knowledge. Thus today enterprises use data mining as an innovative competitive mean. The aim of the study is to determine the importance of data mining applications to capital markets.

Keywords:

Data Mining Capital Markets, Data Mining Methods,

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Akgöbek, Ömer, Çakır Fuat (2009), “Expert System Design with Data Mining”,
Akademic Information Conference, 11-13 February, Harran University, Şanlıurfa, pp.801-806. Albayrak, A.Sait, Yılmaz Şebnem Koltan (2009), “Data Mining: Decision Tree
Algorithms and an Application on Ise Data”, Süleyman Demirel University, The Journal of Faculty of Economics and Administrative Sciences, Vol. 14, No. 1, pp.31-52. Cho, Sungbin, Kim Jinhwa and Bae J. Kwon (2009),“An Integrative Model with
Subject Weight Based on Neural Network Learning for Bankruptcy Prediction”, Expert Systems with Applications, Vol. 36, No. 1, pp.403–410. Kovalerchuk, Boris, Vityaev Evgenii E., (2000), Data Mining In Finance,
Advances in Relational and Hybrid Methods,Newyork: Kluver Academic Publishers. Koyuncugil, A. Serhan (2006). “Fuzzy Data Mining and its Application to Capital
Markets”, Unpublished doctoral dissertation, Ankara University, Ankara. Koyuncugil, A. Serhan (2007), “Determination of Stock Market Corporation’s
Sectoral Risk Profile with Data Mining”, Capital Market Board Resarch Report. Koyuncugil, A. Serhan, Özgülbaş Nilgün (2009),“Risk Modeling by CHAID
Decision Tree Algorithm”. ICCES, Vol. 11, No. 2, pp.39-46. Koyuncugil, A.Serhan, Özgülbaş Nermin (2009), “Data Mining:Data Mining:
Using and Applications in Medicine and Healthcare”, Journal of Information Technology, Vol .2, No. 2, pp.21-32. Larose, D.T., 2005. Discovering Knowledge In Data, An Introduction to Data
Mining, New Jersey: John Wiley & Sons. Newyork Stock Ehxchange (2011), Stock Watch, http://www.nyse.com/glossary/glossarylinks.html?a=1048903219379, [Accessed 02.2011]
Newyork Stock Exchange (2011), http://www.nyse.com/regulation/nyse/1045516499685.html, [Accessed 02.2011]
About NYSE Regulation, Olafsson, Sigurdur, LiXiaonan and Wu, Shuning (2008), “Operations Research and Data Mining”, European Journal of Operational Research, Vol. 187, No. 3, pp. 1429–1448.
Safer, Alan M. (2002), “The Application of Neural Networks to Predict
Abnormal Stock Returns Using Insider Trading Data”, Applied Stochastic Models in Business and Industry,Vol.18, No. 4, pp. 381–389. Sumathi, Sai, Sivanandam S.N., (2006),Introduction to Data Mining and its
Applications, Vol. 29,ISBN 3-540-34350-4. Verlag Berlin Heidelberg: Springer.
The Stock Exchange of Thailand (2011), Investor Protection, http://www.set.or.th/en/regulations/protection/protection_p1.html, 02.2011] Accessed
TWO CROWS (2005), Introduction to Data Mining and Knowledge Discovery,
USA: Two Crows Corporation. Vasilescu, L. Giurca, Siminica Marian, Pirvu Ceraselai, Ionascu Costel, Mehedintu Anca (2011), “Data Mining Used for Analyzing the bankruptcy Risk of the Romanian SMEs”, (in Ali Serhan Koyuncugil and Nermin Özgülbaş- Ed.,
Surveillance Technologies and Early Warning Systems, pp.144-181. Hershey New York: Information Science Reference. Zhang, Dongsong, Zhou Lina(2004), “Discowering Golden Nuggets: Data
Mining in Financial Application”, Ieee Transactıons on Systems, Man, and Cybernetıcs—Part C: Applicatıons and Reviews, Vol. 34, No. 4, pp. 513-522.