Gurjeet Singh
2013-02-01
<p>By comparing historical data of trading like daily Open, High, Low, Close, Volume, Number of Trades, Turnover, Delivery percentage etc. of a particular stock with its Peer Group companies and Non Peer Group companies stocks for a particular period, we can find some unusual observations which are also known as outliers. In this paper we have tried to detect the observations, which are very different from the other observations using a Data Mining Technique for Outlier Detection-“Multiple Linear Regression Analysis”.</p>
https://doi.org/10.5281/zenodo.6047417
oai:zenodo.org:6047417
Zenodo
https://doi.org/10.5281/zenodo.6047416
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Multiple Regression Analysis, Outlier Analysis, Stock Market Fraud Detection, Price Manipulation, NSE, BSE, Indian Stock Market
DETECTION OF OUTLIERS IN STOCK MARKET USING REGRESSION ANALYSIS
info:eu-repo/semantics/article