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On the “mementum” of meme stocks

Author

Listed:
  • Michele Costola

    (University of Ca’ Foscari [Venice, Italy])

  • Matteo Iacopini

    (LUISS - Libera Università Internazionale degli Studi Sociali Guido Carli [Roma])

  • Carlo Romano Marcello Alessandro Santagiustina

    (médialab - médialab (Sciences Po) - Sciences Po - Sciences Po, University of Ca’ Foscari [Venice, Italy])

Abstract

The meme stock phenomenon has yet to be explored. In this note, we provide evidence that these stocks display common stylized facts for the dynamics of price, trading volume, and social media activity. Using a regime-switching cointegration model, we identify the meme stock ''mementum'' which exhibits a different characterization compared to other stocks with high volumes of activity (persistent and not) on social media. Finally, we show that mementum is significant and positively related to the stock's returns. Understanding these properties helps investors and market authorities in their decisions.

Suggested Citation

  • Michele Costola & Matteo Iacopini & Carlo Romano Marcello Alessandro Santagiustina, 2021. "On the “mementum” of meme stocks," Sciences Po Economics Publications (main) hal-04874781, HAL.
    • Handle: RePEc:hal:spmain:hal-04874781
    DOI: 10.1016/j.econlet.2021.110021
    Note: View the original document on HAL open archive server: https://hal.science/hal-04874781v1
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    Cited by:

    1. is not listed on IDEAS
    2. Ilaria Gianstefani & Luigi Longo & Massimo Riccaboni, 2022. "The echo chamber effect resounds on financial markets: a social media alert system for meme stocks," Papers 2203.13790, arXiv.org.
    3. Jones, Jason J., 2021. "A Dataset for the Study of Identity at Scale: Annual Prevalence of American Twitter Users with specified Token in their Profile Bio - 2015-2020," SocArXiv cm5g7, Center for Open Science.
    4. Warkulat, Sonja & Pelster, Matthias, 2024. "Social media attention and retail investor behavior: Evidence from r/wallstreetbets," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    5. Hideyuki Takagi, 2021. "Exploring the Endogenous Nature of Meme Stocks Using the Log-Periodic Power Law Model and Confidence Indicator," Papers 2110.06190, arXiv.org.

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    JEL classification:

    • G50 - Financial Economics - - Household Finance - - - General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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