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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Issue: November 2022

Volume 7 | Issue 11

Impact factor: 8.15

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Paper Title: Machine Language Advancements in Identification of Insider Trading
Authors Name: Divyank Gupta , Saumya Joshi , Samarth Jain , Radhika Baid
Unique Id: IJSDR2211070
Published In: Volume 7 Issue 11, November-2022
Abstract: As Information Technology has progressed over time, issues like noise and multiple data sources have made it a tedious assignment to identify insider trading. A trading is known as illegal insider trading when people privy to the information which is not available to the general public indulge in trading based on this information. They may be people working in the company who have access to confidential information or their relatives, friends or others who have been tipped off about the information. Illegal insider trading might have been going on for decades, but these were going unnoticed in most of the cases. With the development of Machine Learning, it has become possible to design software that has made it easy to assess the data and identify illegal insider trading. In this review paper, we aim to compare the various models that researchers and experts have proposed over time and scale down to the most accurate ones in terms of variety in industry and information.
Keywords: Illegal Insider Trading; Legal Insider Trading; Artificial Intelligence, Machine Learning; Extreme Gradient Boost; SEBI; Decision Tree; Dense Neural Network; Random Forest Classifier.
Cite Article: "Machine Language Advancements in Identification of Insider Trading", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 11, page no.442 - 446, November-2022, Available :http://www.ijsdr.org/papers/IJSDR2211070.pdf
Downloads: 000150694
Publication Details: Published Paper ID: IJSDR2211070
Registration ID:202561
Published In: Volume 7 Issue 11, November-2022
DOI (Digital Object Identifier):
Page No: 442 - 446
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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