Detection of Price Bubbles in Social Media Stock Markets

Authors

Mumtaz Ahmed(1) Mumtaz Ahmed Corresponding author Affiliation COMSATS University, Islamabad, Pakistan Email addressmumtaz.ahmed@comsats.edu.pk Other articles by this author , Aamna Ahmad(2) Aamna Ahmad Affiliation COMSATS University, Islamabad, Pakistan Other articles by this author

  1. COMSATS University, Islamabad, Pakistan
  2. COMSATS University, Islamabad, Pakistan

https://doi.org/10.36923/jcmi.v3i2.490

Ask AI (Dimensions) Download PDF

Abstract

Price bubbles are a common occurrence in the financial and asset markets. There exist numerous studies on detecting price bubbles considering different sectors of countries across the globe, however, very limited work is available on stock price bubbles related to social media. The present research takes a lead and detects multiple and periodically collapsing bubbles in stock prices of four popular social media platforms, namely, Facebook, Pinterest, Snapchat, and Twitter. The empirical analysis is based on the recently developed state of art generalized supremum augmented Dickey-Fully (GSADF) testing approach by Phillips et al. (2015) and it has the advantage of detecting multiple and periodically collapsing bubbles in contrast to rival approaches of bubble detection. The empirical results based on weekly and monthly closing prices spanning over the period 2012 to 2020, provide interesting insights regarding the existence and date stamping of periodically collapsing (multiple) bubbles. The empirical results may be helpful for social media developers and investors to forecast their future decisions.

Article information

Keywords
Generalized Supremum ADFMonte Carlo SimulationRational Commodity Price Theory
Section
Articles
Issue
Vol. 3 No. 2 (2022)
Submitted
November 29, 2022
Accepted
December 31, 2022
Published
December 31, 2022
Corresponding author
Mumtaz Ahmed
Check for updates
Check for updates