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Decrypting Metaverse crypto Market: A nonlinear analysis of investor sentiment

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  • Gunay, Samet
  • Sraieb, Mohamed M.
  • Muhammed, Shahnawaz

Abstract

This study aims to investigate the role of investor sentiment in the emerging metaverse market, a novel entrepreneurship model. Empirical analyses are conducted through various causality tests to reveal the predictive power of investor sentiment on the price developments of the metaverse market. The Nonlinear Granger causality test indicates causal effects running from BTC (Bitcoin), GT (Google Trend), and FGI (Fear-Greed Index) to MVI (Metaverse Index). Further examination of these interactions through MS-VAR analysis reveals that under bear market regimes, both investor sentiment proxies (GT and FGI) and BTC have a statistically significant causal effect on the returns of MVI. This finding suggests that metaverse crypto market returns are substantially influenced by investor sentiment during periods of anxiety and turmoil, evident in steep bear markets, rather than during periods of tranquility and euphoria characteristic of bull markets. The results of the time-varying approach confirm this finding by indicating spikes in causal effects towards the end of 2021, during which a severe crash in cryptocurrency markets occurred. Overall, the causal links during market downturns may stem from the fear of missing out (FOMO) in retail investors, who mainly dominate the sentimental factors utilized in this study.

Suggested Citation

  • Gunay, Samet & Sraieb, Mohamed M. & Muhammed, Shahnawaz, 2024. "Decrypting Metaverse crypto Market: A nonlinear analysis of investor sentiment," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    • Handle: RePEc:eee:finana:v:96:y:2024:i:pb:s105752192400646x
    DOI: 10.1016/j.irfa.2024.103714
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    More about this item

    Keywords

    Metaverse; Investor sentiment; Nonlinear analysis; Cryptocurrency market; Google trend; fear & greed index;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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