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Connectedness across meme assets and sectoral markets: Determinants and portfolio management

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  • Elsayed, Ahmed H.
  • Hoque, Mohammad Enamul
  • Billah, Mabruk
  • Alam, Md. Kausar

Abstract

This study examines the dynamic connectedness and risk spillovers between meme coins, meme stocks, and sectoral markets under different investment horizons. Further, we explore the effects of global uncertainty and risk factors on patterns of dynamic connectedness as well as the benefits of portfolio diversification under different investment strategies. Empirical results indicate that the short-, medium-, and long-term connectedness among these markets are time-varying and are highly responsive to external shocks and stress periods, with the short-term spillover dominating both medium- and long-term spillovers. Furthermore, Meme stocks and coins are net receivers of shock, along with the energy, communication services, utilities, and real estate sectors, whereas other sectors are net transmitters. On the contrary, GameStop-GME becomes net shock transmitters in the medium and long run, while Shiba Inu is a net shock transmitter in the long run. We also show that Meme stocks and Meme coins have distinct features and characteristics from the sectoral markets. They are disconnected and minimally affected by the fluctuations in the sectoral market. Finally, empirical findings show that global risk factors reduce dynamic connectedness across time horizons. These results have several implications for investors, portfolio managers, and policymakers regarding investment strategies, asset allocation, and risk management.

Suggested Citation

  • Elsayed, Ahmed H. & Hoque, Mohammad Enamul & Billah, Mabruk & Alam, Md. Kausar, 2024. "Connectedness across meme assets and sectoral markets: Determinants and portfolio management," International Review of Financial Analysis, Elsevier, vol. 93(C).
  • Handle: RePEc:eee:finana:v:93:y:2024:i:c:s1057521924001091
    DOI: 10.1016/j.irfa.2024.103177
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    Keywords

    Meme stocks; Meme coins; Hedging strategies; Time-frequency spillover; Sectoral market;
    All these keywords.

    JEL classification:

    • 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
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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