One of the most important problems in modern finance is finding efficient ways to summarize and visualize the stock market data to give individuals or institutions useful information about the market behavior for investment decisions. The enormous amount of valuable data generated by the stock market has attracted researchers to explore this problem domain using different methodologies. Potential significant benefits of solving these problems motivated extensive research for years. The research in data mining has gained a high attraction due to the importance of its applications and the increasing generation information. This paper provides an overview of application of data mining techniques such as decision tree. Also, this paper reveals progressive applications in addition to existing gap and less considered area and determines the future works for researchers.

 

Published In : IJCSN Journal Volume 2, Issue 5

Date of Publication : 01 October 2013

Pages : 41 - 46

Figures : 02

Tables : 01

Publication Link : ijcsn.org/IJCSN-2013/2-5/IJCSN-2013-2-5-47.pdf

 

 

 

Radhakrishnan B : Dept. of Computer Science, Baselios Mathews II College of Engineering, Kerala, India.

Shineraj G : Dept. of Computer Science, Baselios Mathews II College of Engineering, Kerala, India.

Anver Muhammed K.M : Dept. of Computer Science, Baselios Mathews II College of Engineering, Kerala, India.

 

 

 

 

 

 

 

Marketing

data mining

decision tree

clustering

 

 

 

With the increase of economic globalization and evolution of information technology, financial data are being generated and accumulated at an unprecedented pace. As a result, there has been a critical need for automated approaches to effective and efficient utilization of massive amount of financial data to support companies and individuals in strategic planning and investment decision making. Data mining techniques have been used to uncover hidden patterns and predict future trends and behaviors in financial markets. The competitive advantages achieved by data mining include increased revenue, reduced cost, and much improved marketplace responsiveness and awareness. This paper therefore recommends various organizations to use data mining techniques in future to resolve complex problems.

 

 

 

 

 

 

 

 

 

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