Herding behavior in cryptocurrencies revisited: Novel evidence from a TVP model

Stavroyiannis, Stavros; Babalos, Vassilios

doi:10.1016/j.jbef.2019.02.007

Cited by 65 publications

(35 citation statements)

References 38 publications

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“…Such evidence can be found at the studies of: Bouri et al. (2019) , Stavroyiannis and Babalos (2019) , and Vidal-Tomas et al. (2019) .…”

Section: Studies Revealing Herding Behaviour In Digital Currency Markmentioning

confidence: 60%

“…The static model finds no evidence of herding while probit results support that higher uncertainty intensifies herding phenomena. Moreover, Stavroyiannis and Babalos (2019) employ Ordinary Least Squares (OLS), the time-varying parameter (TVP) and quantile regression methodologies in order to trace herding behaviour in virtual currencies from 9 August 2015 until 18 February 2018. Moreover, the CSSD and CSAD specifications are employed.…”

Section: Studies Revealing Herding Behaviour In Digital Currency Markmentioning

confidence: 99%

“…In an overall sense, there is that Bitcoin remains among the most influential cryptocurrencies though the level of this dominance and the periods during which this exerts herding effects is not unanimous across studies. Most relevant papers indicate that herding is stronger during bull markets ( Kallinterakis and Wang, 2019 ; Stavroyiannis and Babalos, 2019 ) but there are also fewer studies that support higher herding intensity during bear markets ( Vidal-Tomas et al., 2019 ). The periods of high herding influences vary substantially as concerns their duration.…”

Section: Studies Revealing Herding Behaviour In Digital Currency Markmentioning

confidence: 99%

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Herding behaviour in digital currency markets: An integrated survey and empirical estimation

Kyriazis

2020

Heliyon

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This paper reviews the empirical literature on the highly popular phenomenon of herding behaviour in the markets of digital currencies. Furthermore, a comparison takes place with outcomes from earlier studies about traditional financial assets. Moreover, we empirically investigate herding behaviour of 240 cryptocurrencies during bull and bear markets. The present survey suggests that empirical findings about whether herding phenomena have made a significant appearance or not in cryptocurrency markets are split. The Cross-sectional absolute deviations (CSAD) and Cross-sectional standard deviations (CSSD) approaches for measuring herding tendencies are found to be the most popular. Different behaviour is detected in bull periods compared to bear markets. Nevertheless, evidence from primary studies indicates that herding is stronger during extreme situations rather than in normal conditions. However, our empirical estimations reveal that herding behaviour is evident only in bull markets. These findings cast light on and provide a roadmap for investment decisions with modern forms of liquidity.

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“…Such evidence can be found at the studies of: Bouri et al. (2019) , Stavroyiannis and Babalos (2019) , and Vidal-Tomas et al. (2019) .…”

Section: Studies Revealing Herding Behaviour In Digital Currency Markmentioning

confidence: 60%

Section: Studies Revealing Herding Behaviour In Digital Currency Markmentioning

confidence: 99%

Section: Studies Revealing Herding Behaviour In Digital Currency Markmentioning

confidence: 99%

See 1 more Smart Citation

Herding behaviour in digital currency markets: An integrated survey and empirical estimation

Kyriazis

2020

Heliyon

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“…In cryptocurrency trading, it was found that no herding activities as a trader may have an individual motive for cryptocurrency trading (Stavros &Vassilios, 2019). This may imply that there is no conspiracy in cryptocurrency trading.…”

Section: Previous Research On Cryptocurrencymentioning

confidence: 99%

“…This is experimental to gamblers. Other researchers found that there were no herding activities in cryptocurrency trading as a trader may have an individual motive for cryptocurrency trading (Stavros and Vassilios, 2019). Meanwhile, Bouri et al (2019) found a tendency of herding when uncertainty increased, which may cause cartel trading.…”

Section: Introductionmentioning

confidence: 96%

The requirements of cryptocurrency for money, an Islamic view

Siswantoro

Handika

Mita

2020

Heliyon

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This research aims to evaluate the suitability of cryptocurrency as money from the Islamic perspective. Money, in the Islamic perspective, has specific characteristics and requirements, such as stability and is based on assets. Cryptocurrency may not fulfil this as it has queries as money from the Islamic perspective. The research method applied data of 23 cryptocurrency prices and related information. The result shows that cryptocurrency is hugely volatile and has limits to being called 'money,' as it is limited and used for speculation, which is prohibited in Islam. The research implies that Muslims would be reluctant to use cryptocurrency as money, as a currency of transaction. This reason raise an expectation that the cryptocurrency will not develop rapidly in Muslim countries.

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Is cryptocurrency Efficient? A High-Frequency Asymmetric Multifractality Analysis

Meng¹,

Khan

2023

Comput Econ

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Herding behavior in cryptocurrencies revisited: Novel evidence from a TVP model

Cited by 65 publications

References 38 publications

Herding behaviour in digital currency markets: An integrated survey and empirical estimation

Herding behaviour in digital currency markets: An integrated survey and empirical estimation

The requirements of cryptocurrency for money, an Islamic view

Is cryptocurrency Efficient? A High-Frequency Asymmetric Multifractality Analysis

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