TITLE:
Exploring the Endogenous Nature of Meme Stocks Using the Log-Periodic Power Law Model and Confidence Indicator
AUTHORS:
Hideyuki Takagi
KEYWORDS:
Market Crash, Financial Bubble, Endogenous Nature, Log-Periodic Power Law Model, Meme Stock
JOURNAL NAME:
Journal of Mathematical Finance,
Vol.12 No.1,
February
24,
2022
ABSTRACT: This study examined the endogenous nature of negative bubbles forming in meme stocks with the Log-Periodic Power Law (LPPL) Confidence Indicator (CI). A meme stock is a stock that has gained a significant amount of attention on a large social media platform such as Yahoo! or Reddit. This study examined four meme stocks including Tesla, Inc. (TSLA), GameStop Corp. (GME), Koss Corporation (KOSS), and AMC Entertainment Holdings Inc (AMC). The CI was able to detect numerous bubbles forming in meme stocks, but had difficulty in significantly predicting social media-induced exogenous rallies. This may have been due to price movements affected by external causes such as short squeezes. However, the model did provide proof for the formation of previous bubbles that could have been a catalyst for the meme stocks rallies. This study outlines the real unpredictability of many black-swan events, and further studies could be done examining exogenous bubbles.