Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India

Research Article

Intelligent System for the Detection of Insider Trading in Indian Stock Market

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  • @INPROCEEDINGS{10.4108/eai.7-12-2021.2314574,
        author={Amosh  Sapkota and Anand  Kumar and Anjali  Mathur},
        title={Intelligent System for the Detection of Insider Trading in Indian Stock Market},
        proceedings={Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India},
        publisher={EAI},
        proceedings_a={ICCAP},
        year={2021},
        month={12},
        keywords={insider trading security market sebi corporate filing nse nifty 50 financial results machine learning deep learning},
        doi={10.4108/eai.7-12-2021.2314574}
    }
    
  • Amosh Sapkota
    Anand Kumar
    Anjali Mathur
    Year: 2021
    Intelligent System for the Detection of Insider Trading in Indian Stock Market
    ICCAP
    EAI
    DOI: 10.4108/eai.7-12-2021.2314574
Amosh Sapkota1,*, Anand Kumar1, Anjali Mathur1
  • 1: KoneruLakshmaiah Education Foundation
*Contact email: amoshsapkota@gmail.com

Abstract

Insider trading is a pervasive stock market malpractice that has existed since the inception of the security market. Insider trading is notoriously difficult for regulators worldwide to crack down on. In our investigation, we proposed a methodology for detection of insider trading in Indian stock market. To start with, the insider trading cases that happened in the Indian financial exchange we collected corporate filing data from NSE website for each company of NIFTY 50, which has different columns related to price, action and person or organization doing that action from 1stJanuary to a day prior to the publicationof financial results of December quarter offiscal year 2020-21. On doing as such, we have seen that enormous exchange have been done prior to publicationof financial results in some companies, which can be suspected as insider trading. At that point, themachine learning algorithms were utilized for preparing and for foreseeing Insider trading. Then, the algorithms were used for training and for predicting insider trading. Finally, their performance wasmeasured, compared and accuracy was calculated.Experiments revealed that the recommended method successfully achieved the best accuracy. This could be amazingly helpful for detecting insider trading in future, not only in Indian stock market, but also in other stock exchanges.