Special Issue on Data Mining in Financial Application

For the last few years, data mining has emerged from several historically disjoint fields, such as statistics, information systems, artificial intelligence, knowledge discovery. Data mining refers to the methods for the intelligent analysis of large data sets, used to discover hidden knowledge, unknown patterns and rules for a variety of decision making activity. Data mining in financial application can predict the trends and behaviors in the future of the financial markets, result in an improvement of market place responsiveness and awareness leading to reduced costs and increased revenue.

In this special issue, we intend to invite front-line researchers and authors to submit original research and review articles on exploring data mining in financial application. Potential topics include, but are not limited to:

• Financial model evaluation and testing
• Building prediction and trading models
• Financial data classification
• Affinity grouping or association rules in finance
• Financial data clustering
• Data mining in risk management
• Data mining and knowledge discovery

Authors should read over the journal’s For Authors carefully before submission. Prospective authors should submit an electronic copy of their complete manuscript through the journal’s Paper Submission System.

Please kindly specify the “Special Issue” under your manuscript title. The research field “Special Issue – Data Mining in Financial Application” should be selected during your submission.

According to the following timetable:

Guest Editor:

For further questions or inquiries

Please contact Editorial Assistant at

jdaip@scirp.org