Cryptocurrencies’ Price Crash Risk and Crisis Sentiment

Anastasiou, Dimitrios; Ballis, Antonis; Δράκος, Κωνσταντίνος

doi:10.1016/j.frl.2021.101928

Cited by 31 publications

(18 citation statements)

References 20 publications

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“…Control variables are the natural log of VIX, EPU and UCRY. Kalyvas et al (2020) and Anastasiou et al (2021), together with much of the relevant stock market literature, use ordinary least squares (OLS) regression to examine crash risk. This provides an estimate of the conditional mean response of crash risk.…”

Section: Empirical Analysismentioning

confidence: 99%

“…As in Kalyvas et al (2020) and Anastasiou et al (2021), we adopt two crash-risk measures that originated in the stock price crash literature (Chen et al , 2001). Our first measure is the negative coefficient of skewness ( NCSKEW ) of returns.…”

Section: Datamentioning

confidence: 99%

“…In focusing on cryptocurrency crash risk, our paper is directly related to the work of Kalyvas et al (2020) and Anastasiou et al (2021). Kalyvas et al (2020) consider the relationship of Bitcoin price crash risk for a set of uncertainty measures and behavioural factors which are obtained from Thomson Reuters Marketpsych Indices.…”

Section: Introductionmentioning

confidence: 99%

“…It is therefore important to understand investor behaviour in other cryptocurrencies which have gained in popularity. This is partly addressed by Anastasiou et al (2021) who find that price crash risk for a set of the largest cryptocurrencies is positively related to a FEARS sentiment index. While our paper focuses on a similar set of cryptocurrencies, we focus on investor attention rather than investor sentiment .…”

Section: Introductionmentioning

confidence: 99%

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Investor attention and cryptocurrency price crash risk: a quantile regression approach

Smales

2022

SEF

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Purpose Motivated by the lure of cryptocurrencies for retail investors, whose concentrated holdings are particularly exposed to price crash risk, this paper aims to study the relationship between investor attention and crash risk for a range of cryptocurrencies. Design/methodology/approach This study adopts a quantile regression approach to determine the effect of investor attention on crash risk. Crash risk is measured using the negative coefficient of skewness and down up volatility. Findings This study finds that the connection is concentrated in the tails of the crash risk distribution. Investor attention has a positive relationship with crash risk when crash risk is low (below-median quantiles) and negative when crash risk is high (above-median). The findings are consistent for different measures of crash risk, for alternate internet searches and for a panel of large cryptocurrencies in addition to Bitcoin. This study also notes seasonality in crash risk, with higher crash risk during the June–August period and lower crash risk in the Halloween period that runs from November to April. Originality/value The results provide insights that are not apparent in previous analyses of cryptocurrency price crash risk. The results are particularly important for retail investors, who constitute a large portion of the cryptocurrency market, as they tend to hold concentrated investments and so a price crash of a single asset may have a large bearing on their wealth.

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Section: Empirical Analysismentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Investor attention and cryptocurrency price crash risk: a quantile regression approach

Smales

2022

SEF

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“…However, a fast-growing literature has supported that private sector bank deposits are also affected by agents' economic sentiment, with some researchers support that sentiment exerts a higher impact on bank deposits than macro fundamentals. Our work is part of a growing strand of the literature that explores how the economic sentiment affects various facets of the economic activity (see among others, (Anastasiou, Ballis, & Drakos, 2021a, 2021cAnastasiou, Bragoudakis, & Giannoulakis, 2021b;Schumaker, Zhang, Huang, & Chen, 2012;Smales, 2014)) and especially to the literature investigating the impact of sentiment on bank deposits Anastasiou & Katsafados, 2020;Fecht, Thum, & Weber, 2019).…”

Section: Introductionmentioning

confidence: 99%

On the Construction of a Leading Indicator Based on News Headlines for Predicting Greek Deposit Outflows

Anastasiou

Petralias

2021

2641-5313

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Employing data in a monthly frequency, with a sample period spanning from 2002 to 2018, the purpose of this study is twofold. First, we construct a novel leading indicator based on news headlines drawn from Bloomberg, and second, examine whether this leading indicator able to capture agents’ sentiment affects Greek bank deposit flows’ trajectory. Employing alternative econometric methodologies, we find that this index proxies for depositors’ crisis sentiment and the higher this index becomes, the higher the depositors’ negative sentiment becomes, leading them to withdraw their bank deposits. Overall, in this work, we show that the last decade’s advances in internet technology, which permit us to have direct access to a vast amount of information such as news headlines, offers the possibility of forecasting critical measures in the economy’s banking system, such as the number of bank deposits, which are of crucial importance. Monetary poly authorities or macroprudential regulators could adapt our model to assess the resilience of a bank or the whole banking sector.

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Cryptocurrency market microstructure: a systematic literature review

Almeida,

Gonçalves

2023

Ann Oper Res

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This study contributes to the unconsolidated cryptocurrency literature, with a systematic literature review focused on cryptocurrency market microstructure. We searched Web of Science database and focused only on journals listed on 2021 ABS list. Our final sample comprises 138 research papers. We employed a quantitative and an integrative analysis, and revealed complex network associations, and a detailed research trending analysis. Our study provides a robust and systematic contribution to cryptocurrency literature by making use of a powerful and accurate methodology—the bibliographic coupling, also by only considering ABS academic journals, using a wider keyword scope, and not enforcing any restrictions regarding areas of knowledge, thus enhancing the contribution of extant literature by allowing the insights of more high-quality peripheral studies on the subject. The conclusions of this study are of extreme importance for researchers, investors, regulators, and the academic community in general. Our study provides high structured networking and clear information for research outlets and literature strands, for future studies on cryptocurrency investment, it also presents valuable insights to better understand the cryptocurrency market microstructure and deliver helpful information for regulators to effectively regulate cryptocurrencies.

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Cryptocurrencies’ Price Crash Risk and Crisis Sentiment

Cited by 31 publications

References 20 publications

Investor attention and cryptocurrency price crash risk: a quantile regression approach

Investor attention and cryptocurrency price crash risk: a quantile regression approach

On the Construction of a Leading Indicator Based on News Headlines for Predicting Greek Deposit Outflows

Cryptocurrency market microstructure: a systematic literature review

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