Predicting Aramco’s IPO Long-Term Performance During COVID Times

Mohammad Imdad Haque, Master Prince, Abdul Rahman Shaik

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper aims to assess whether the outbreak of the highly contagious pandemic had an impact on the share prices of recently listed Aramco in light of the Fads hypothesis using the methods of neural network and ARIMA. The IPO of Aramco, the world’s largest oil company, was a much-hyped affair. Given the relevant importance of the company, it was expected that Aramco's share prices would not underperform in the long run. But the analysis indicates the opposite. The study uses two time periods using the announcement of the pandemic by the World Health Organization as the threshold date to see the impact of the pandemic on Aramco’s share prices. The forecasting results validate the Fads hypothesis implying that Aramco’s share prices would have underperformed in the long run, even in the absence of a pandemic outbreak. Finally, the study cautions investors against the hype created by IPOs.

Original languageEnglish
Title of host publicationProceedings of Data Analytics and Management - ICDAM 2022
EditorsAshish Khanna, Zdzislaw Polkowski, Oscar Castillo
PublisherSpringer Science and Business Media Deutschland GmbH
Pages69-80
Number of pages12
ISBN (Print)9789811976148
DOIs
StatePublished - 2023
EventInternational Conference on Data Analytics and Management, ICDAM 2022 - Jelenia Góra, Poland
Duration: 25 Jun 202226 Jun 2022

Publication series

NameLecture Notes in Networks and Systems
Volume572
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceInternational Conference on Data Analytics and Management, ICDAM 2022
Country/TerritoryPoland
CityJelenia Góra
Period25/06/2226/06/22

Keywords

  • ARIMA
  • Coronavirus
  • Impresario hypothesis
  • Initial public offer
  • Neural network

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