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

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  • Biswajit Acharjya

    (VIT Business School, VIT, Vellore, India)

  • Subhashree Natarajan

    (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.

Suggested Citation

  • Biswajit Acharjya & Subhashree Natarajan, 2019. "A Fuzzy Rough Feature Selection Framework for Investors Behavior Towards Gold Exchange-Traded Fund," International Journal of Business Analytics (IJBAN), IGI Global, vol. 6(2), pages 46-73, April.
    • Handle: RePEc:igg:jban00:v:6:y:2019:i:2:p:46-73
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    Cited by:

    1. Li, Sufang & Xu, Qiufan & Lv, Yixue & Yuan, Di, 2022. "Public attention, oil and gold markets during the COVID-19: Evidence from time-frequency analysis," Resources Policy, Elsevier, vol. 78(C).

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