A Fuzzy Rough Feature Selection Framework for Investors Behavior Towards Gold Exchange-Traded Fund

Author:

Acharjya Biswajit1,Natarajan Subhashree1

Affiliation:

1. VIT Business School, VIT, Vellore, India

Abstract

Behavioural finance has gained research interest among researchers because of investor behavior and market anomalies. Investor behaviour varies with demographics and geographic characteristics. Further, investor behavior towards a gold exchange trade fund is gaining research interest due to various factors. Not much research has been carried out in this direction, with the exception of some comparisons. Therefore, the performance of a gold exchange traded fund needs to be assessed from the investor behavior perspective. Additionally, the investors behavior contains uncertainties. Thus, there is a need for intelligent techniques for identifying the investors behavior despite the presence of uncertain behavioral characteristics. Therefore, to study uncertain behavior characteristic in gold exchange traded fund, in this article the authors employ a fuzzy rough set. They employ fuzzy rough quick reduct algorithm to find the superfluous attributes. Further decision rules are generated to identify the chief feature of investors' behavior towards gold exchange traded fund.

Publisher

IGI Global

Subject

Strategy and Management,Business and International Management

Reference47 articles.

1. Acharjya, D. P. (2013). Rough computing based information retrieval in knowledge discovery databases. In Information and Knowledge Management-Tools, Techniques and Practices (pp. 123-153).

2. Knowledge Extraction from Information System Using Rough Computing

3. Acharjya, D. P., & Bhattacharjee, D. (2013). A rough computing based performance evaluation approach for educational institutions. International Journal of Software Engineering and Its Applications, 7(4), 331-348. arXiv:1308.0725

4. A framework for attribute selection in marketing using rough computing and formal concept analysis

5. Prediction of Missing Associations Using Rough Computing and Bayesian Classification

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