TY - GEN
T1 - Predicting Aramco’s IPO Long-Term Performance During COVID Times
AU - Imdad Haque, Mohammad
AU - Prince, Master
AU - Shaik, Abdul Rahman
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - ARIMA
KW - Coronavirus
KW - Impresario hypothesis
KW - Initial public offer
KW - Neural network
UR - http://www.scopus.com/inward/record.url?scp=85152548123&partnerID=8YFLogxK
U2 - 10.1007/978-981-19-7615-5_6
DO - 10.1007/978-981-19-7615-5_6
M3 - Conference contribution
AN - SCOPUS:85152548123
SN - 9789811976148
T3 - Lecture Notes in Networks and Systems
SP - 69
EP - 80
BT - Proceedings of Data Analytics and Management - ICDAM 2022
A2 - Khanna, Ashish
A2 - Polkowski, Zdzislaw
A2 - Castillo, Oscar
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Data Analytics and Management, ICDAM 2022
Y2 - 25 June 2022 through 26 June 2022
ER -