Herd behaviour in the cryptocurrency market: Fundamental vs. spurious herding

Senarathne, Chamil W.; Jiang, Wei

doi:10.5937/ejae17-22053

Cited by 12 publications

(9 citation statements)

References 42 publications

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“…All these 83 cryptocurrencies are taken for study. The CCI-30 index is used as a surrogate for the crypto market index (Ajaz and Kumar, 2018; Senarathne and Jianguo, 2020). Also, S&P 500 (USA), S&P BSE Sensex (India) and MERVAL (Argentina) are taken as proxies for advanced, emerging and frontier stock markets, respectively, for the aforementioned sample period.…”

Section: Methodsmentioning

confidence: 99%

Herding in the crypto market: a diagnosis of heavy distribution tails

Shrotryia

Kalra

2021

RBF

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PurposeWith the unprecedented growth of digitalization across the globe, a new asset class, that is cryptocurrency, has emerged to attract investors of all stripe. The novelty of this newly emerged asset class has led researchers to gauge anomalous trade patterns and behavioural fallacies in the crypto market. Therefore, the present study aims to examine the herd behaviour in a newly evolved cryptocurrency market during normal, skewed, Bitcoin bubble and COVID-19 phases. It, then, investigates the significance of Bitcoin in driving herding bias in the market. Finally, the study gauges herding contagion between the crypto market and stock markets.Design/methodology/approachThe study employs daily closing prices of cryptocurrencies and relevant stocks of S&P 500 (USA), S&P BSE Sensex (Index) and MERVAL (Argentina) indices for a period spanning from June 2015 to May 2020. Quantile regression specifications of Chang et al.’s (2000) absolute deviation method have been used to locate herding bias. Dummy regression models have also been deployed to examine herd activity during skewed, crises and COVID-19 phases.FindingsThe descriptive statistics reveal that the relevant distributions are leptokurtic, justifying the selection of quantile regression to diagnose tails for herding bias. The empirical results provide robust evidence of crypto herd activity during normal, bullish and high volatility periods. Next, the authors find that the assumptions of traditional financial doctrines hold during the Bitcoin bubble. Further, the study reveals that the recent outbreak of COVID-19 subjects the crypto market to herding activity at quantile (t) = 0.60. Finally, no contagion is observed between cryptocurrency and stock market herding.Practical implicationsDrawing on the empirical findings, it is believed that in this age of digitalization and technological escalation, this new asset class can offer diversification benefits to the investors. Also, the crypto market seems quite immune to behavioural idiosyncrasies during turbulence. This may relieve regulators of the possible instability this market may pose to the entire financial system.Originality/valueThe present study appears to be the first attempt to diagnose leptokurtic tails of relevant distribution for crypto herding in the wake of two remarkable events: the crypto asset bubble (2016–2017) and the outbreak of coronavirus (early 2020).

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Section: Methodsmentioning

confidence: 99%

Herding in the crypto market: a diagnosis of heavy distribution tails

Shrotryia

Kalra

2021

RBF

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“…Interestingly, in the cryptocurrency market, there has been no significant change in behavior leading to at least recorded until March 2020 (Yarovaya et al, 2020). Although in practice the cryptocurrency market has no linkage with global markets (Giudici et al, 2020), they are concentrated and thus may not spontaneously be compared with traditional financial market behavior in terms of herding behavior (Senarathne & Wei, 2020). Further assessment is needed to consider the herding behavior that seems unusual.…”

Section: Herding Behaviormentioning

confidence: 99%

Financial Behavior during COVID-19: Cognitive Errors That Can Define Financial Future

Putri¹,

Xu²,

Akwetteh³

2020

JSS

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Purpose: The purpose of this study is to determine the economic effects caused by the crisis impact of the COVID-19 pandemic. Methodology: We explored various kinds of literature from various journals to find out the level of trust and financial behavior of the public during the COVID-19 pandemic. Results and findings: The phenomena that occurred during the crisis due to the COVID-19 pandemic, such as excessive volatility and the confidence of unaffected financial institutions, cannot be explained through the traditional market paradigm. In this paper, we explore this phenomenon from a behavioral finance perspective and discuss some relevant cognitive errors and biases during and after the crisis due to the COVID-19 pandemic. Limitation:The study explains by exploring the phenomenon from the viewpoint of financial behavior and discussing some of the relevant cognitive errors during and after the crisis. We only look at each phenomenon from a psychological point of view and consider its relevance to financial institutions and markets as well as the financial crisis due to the COVID-19 Pandemic.

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“…Herding behavior can be defined as the act of copying the investment actions of other investors in the market (Senarathne & Jianguo, 2020). The presence of herding behavior in a financial market can cause a gap between the actual value of a stock in the market and its intrinsic value (BenSaï da, Jlassi, & Litimi, 2015).…”

Section: Herding Behaviormentioning

confidence: 99%

Remeasuring Sectoral Herding in the Financial Markets

Elshqirat¹

2020

IBR

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Herding behavior was concluded to exist in some sectors and under some market conditions in the Jordanian stock market when measured using the cross-sectional absolute deviation. The purpose of this study was to retest the existence of the sectoral herding using the cross-sectional dispersion of betas and compare the results with those reached using the measure of the cross-sectional absolute deviation. Behavioral finance theory represents the main base on which this study was built. In this study, the researcher tried to answer questions related to whether herding behavior exists in the Jordanian market and its sectors if measured using cross-sectional dispersion of betas and whether results will be different from those reached using other measures. In this quantitative study, data from Amman stock exchange were used and the period covered was from 2000 to 2018. These data were used to calculate the cross-sectional dispersion of betas which was tested using t-test, Kruskal–Wallis test, Mann-Whitney U test, and Wilcoxon Signed-Rank test. Results indicated that herding behavior existed in market and in each sector at the same level which was not affected by the financial crisis. Furthermore, the study revealed that herding level was the same when the market (sector) was rising and when it was falling and this similarity has not been changed by the occurrence of the global financial crisis. Finally, results indicated that herding was at its lowest level in the entire market and in the industrial sector during the time of financial crisis. These results are different from those of the study conducted in Jordan using cross-sectional absolute deviation which implies that using different herding measures yields different results.

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Herd behaviour in the cryptocurrency market: Fundamental vs. spurious herding

Cited by 12 publications

References 42 publications

Herding in the crypto market: a diagnosis of heavy distribution tails

Herding in the crypto market: a diagnosis of heavy distribution tails

Financial Behavior during COVID-19: Cognitive Errors That Can Define Financial Future

Remeasuring Sectoral Herding in the Financial Markets

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