Determination of IPOS out Performance through Logistic Regression Analysis
R.Selvamathi1, A.A.Ananth2
1R.Selvamathi, Department of Business Administration, Annamalai University India.
2A.A.Ananth, Department of Business Administration, Annamalai University India
Manuscript received on 08 April 2019 | Revised Manuscript received on 15 April 2019 | Manuscript Published on 26 April 2019 | PP: 656-659 | Volume-8 Issue-6S April 2019 | Retrieval Number: F61470486S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This study analyzed empirically evaluate the IPOs independent variables for long run of outperformance observed the effects of factor impact through secondary data of IPOs and the data was collected from NSE. In that the factor impact of IPOs are evaluated Lead time, Issue size, Issue price and IPO Grade, in influencing the IPO performance by buy and hold abnormal raw return on listing day and various timeframes in the long run as well as their influence on outperformance using logistic regression analysis of IPOs was observed that the values of independent variables in the logistic regression.
Keywords: Factor Impact, Long Run, Lead Time, Issue Size, Issue Price, IPO Grade, Abnormal Raw Returns, Outperformance, Logistic Regression.
Scope of the Article: Big Data Analytics and Business Intelligence