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• We investigate the impact of the crypto fear and greed index (FGI) on the price synchronicity of major cryptocurrencies. • We use the realized correlation (RC) to measure price synchronicity. • The relationship between FGI and RC is U-shaped. • This relationship is robust to an alternative R 2-based synchronicity measure. In this study, we use intraday data on Bitcoin, Ethereum, Litcoin, and Monero, traded on the Bitfinex exchange, to investigate the impact of the crypto fear and greed index (FGI) on the pairwise price synchronicity of these cryptocurrencies. Based on data from February 2018 to June 2023, our results show that the relationship between investors' collective sentiment (the FGI) and price synchronicity (as measured by the realized correlation) exhibits a U-shaped pattern rather than a linear one. This is the first study to document a U-shaped relationship between FGI-based online investor sentiment and the price synchronicity of cryptocurrencies. [ABSTRACT FROM AUTHOR]

Motivated by the recent literature on cryptocurrency volatility dynamics, this paper adopts the ARJI, GARCH, EGARCH, and CGARCH models to explore their capabilities to make out-of-sample volatility forecasts for Bitcoin returns over a daily horizon from 2013 to 2018. The empirical results indicate that the ARJI jump model can cope with the extreme price movements of Bitcoin, showing comparatively superior in-sample goodness-of-fit, as well as out-of-sample predictive performance. However, due to the excessive volatility swings on the cryptocurrency market, the realized volatility of Bitcoin prices is only marginally explained by the GARCH genre of employed models. [ABSTRACT FROM AUTHOR]

This article examines the asymmetric volatility spillover effects between Bitcoin and alternative coin markets at the disaggregate level. We apply a frequency connectedness approach to the daily data of 11 major cryptocurrencies for the period from 1 September 2017 to 2 March 2022. We try to uncover the existence of the "fear of missing out" psychological effect and "pump-and-dump schemes" in the crypto markets. To do that, we estimate the volatility spillovers from Bitcoin to altcoin and the cryptos' own risk spillovers during bull and bear markets. The spillover results from Bitcoin to altcoin provide mixed results regarding the presence of this theory for major cryptocurrencies. However, the empirical findings carried out by the cryptos' own spillover effects fully confirm the existence of a fear-of-missing-out effect and pump-and-dump schemes in all cryptocurrencies except for USDT. [ABSTRACT FROM AUTHOR]