Decrypting Metaverse crypto Market: A nonlinear analysis of investor sentiment

IF 7.5 1区 经济学 Q1 BUSINESS, FINANCE
Samet Gunay , Mohamed M. Sraieb , Shahnawaz Muhammed
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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.
解密 Metaverse 加密货币市场:投资者情绪的非线性分析
本研究旨在探讨投资者情绪在新兴的元宇宙市场这一新型创业模式中的作用。通过各种因果检验进行实证分析,揭示投资者情绪对元宇宙市场价格发展的预测力。非线性格兰杰因果检验表明,从 BTC(比特币)、GT(谷歌趋势)和 FGI(恐惧-贪婪指数)到 MVI(元宇宙指数)之间存在因果效应。通过 MS-VAR 分析对这些交互作用的进一步研究表明,在熊市制度下,投资者情绪代用指标(GT 和 FGI)和 BTC 对 MVI 的收益都有统计上显著的因果影响。这一发现表明,在焦虑和动荡时期,而不是在牛市特有的平静和兴奋时期,元海外加密货币市场的回报会受到投资者情绪的重大影响,这在暴跌的熊市中很明显。时变方法的结果证实了这一结论,表明因果效应在 2021 年底达到峰值,在此期间加密货币市场发生了严重崩盘。总体而言,市场低迷期间的因果联系可能源于散户投资者对错过的恐惧(FOMO),而散户投资者在本研究使用的情感因素中占主导地位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
10.30
自引率
9.80%
发文量
366
期刊介绍: The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.
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