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Viral Trends and Stock Markets: Spillover Between Meme Assets and Sectoral Returns

Author

Listed:
  • Barbić Tajana

    (Institute of Economics, Zagreb, Croatia)

  • Čondić-Jurkić Iva

    (Rochester Institute of Technology, Croatia)

Abstract

Meme assets are a unique and modern phenomenon in the stock market, characterized by social media-driven hype and significant price volatility. The aim of this paper is to explore the relationships between meme assets and sectoral dynamics. We employ the Granger causality test to examine predictive relationships between daily returns of GameStop and five meme exchange traded funds and eleven sector index funds. Our results show that selected meme assets have relatively limited impact on various sectoral indices and vice versa, suggesting that meme stocks and meme ETFs can offer diversification benefits for sectoral investments. These findings offer insights to investors in designing their approaches to investment strategies and portfolio management, as well as regulators in their attempt to ensure financial market stability.

Suggested Citation

  • Barbić Tajana & Čondić-Jurkić Iva, 2024. "Viral Trends and Stock Markets: Spillover Between Meme Assets and Sectoral Returns," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 20(4), pages 1-15.
    • Handle: RePEc:vrs:finiqu:v:20:y:2024:i:4:p:1-15:n:1001
    DOI: 10.2478/fiqf-2024-0023
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    More about this item

    Keywords

    Meme Stocks; Meme ETFs; Sectoral Indices;
    All these keywords.

    JEL classification:

    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • 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

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