Regime-dependent herding behavior in Asian and Latin American stock markets

Kabir, M. Humayun; Shakur, Shamim

doi:10.1016/j.pacfin.2017.12.002

Cited by 54 publications

(33 citation statements)

References 68 publications

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“…Herding behaviour is defined by Banerjee (1992) as the action of doing what others are doing without using one's own information. This behaviour bias leads to excessive volatility in financial markets, with short term trends (Humayun Kabir & Shakur, 2018). Consequently, speculative bubbles and crashes are created from repeated behavioural scenarios.…”

Section: Introduction 11 Backgroundmentioning

confidence: 99%

Islamic, Green, and Conventional Cryptocurrency Market Efficiency During the Covid-19 Pandemic

Mnif

Jarboui

2021

JIMF

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Unlike conventional cryptocurrencies, Islamic ones are new technologies backed by tangible assets and are characterised by their fundamental values. After the COVID-19 outbreak, cryptocurrency responses have shown different behaviour to stock market reactions. However, there is a lack of studies on the efficiency of Islamic and green cryptocurrencies during the pandemic. This paper attempts to analyse the behaviour of three typical families of cryptocurrencies (conventional, Islamic, and green) extracted according to their availability in daily frequencies during COVID-19. For this purpose, their efficiency levels are studied before and after the outbreak by employing multifractal detrended fluctuation analysis (MFDFA) to make the best predictions and strategies. The inefficiency of the cryptocurrencies is assessed through a magnitude of long-memory (MLM) efficiency index, and the impact of COVID-19 on their efficiency is evaluated. The primary results show that HelloGold was the most efficient market before the COVID-19 outbreak and that subsequently Ethereum has been the mostefficient. In addition, the findings reveal that the cryptocurrency reactions are not similar and show more resilience in the Ethereum and Litecoin markets than in other cryptocurrency markets. The main contribution of this study is the evaluation of the impact of COVID-19 on the various classes of crypto money. This work has practical implications, as it provides new insights into trading opportunities and market reactions. Moreover, he work has theoretical implications based on its evaluation of three distinct models from different doctrine viewpoints.

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Section: Introduction 11 Backgroundmentioning

confidence: 99%

Islamic, Green, and Conventional Cryptocurrency Market Efficiency During the Covid-19 Pandemic

Mnif

Jarboui

2021

JIMF

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“…The first is that herding effect should be further explored in other aspects of human society. Previous studies have found herding effect in consumer behaviors (Chen et al, 2010; Moraes, 2016; Gao et al, 2017), stock markets (Chiang and Zheng, 2010; Blake et al, 2017; Kabir and Shakur, 2018), housing markets (Ngene et al, 2017), and group incidents (Xiong et al, 2016). The present study preliminarily indicated the existence of herding effect in business decisions.…”

Section: Discussionmentioning

confidence: 95%

“…Currently, this concept is also used to describe particular social phenomena, in which people are strongly influenced by others’ decisions and follow behaviors of others in the same group (Asch, 1956; Banerjee, 1992). In fact, herding effect widely exists in human society and has been found in consumer behavior (Chen et al, 2010; Moraes, 2016; Gao et al, 2017), stock markets (Chiang and Zheng, 2010; Blake et al, 2017; Kabir and Shakur, 2018), housing markets (Ngene et al, 2017), and group incidents (Xiong et al, 2016). In past decades, a large number of studies have explored the determinants of herding effect and its impact on individual decisions and behaviors using surveys and behavioral tests (Banerjee, 1992; Cipriani and Guarino, 2005; Chen, 2008; Pierdzioch and Stadtmann, 2010; Huang et al, 2015; Chong et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

The Neural Basis of Herding Decisions in Enterprise Clustering: An Event-Related Potential Study

et al. 2019

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Herding behavior refers to the social phenomenon in which people are intensely influenced by the decisions and behaviors of others in the same group. Although several recent studies have explored the neural basis of herding decisions in people’s daily lives (e.g., consumption decisions), the neural processing of herding decisions underlying enterprise behavior is still unclear. To address this issue, this study extracted event-related potentials (ERPs) from electroencephalographic data when participants (i.e., top executives in real enterprises) performed a choice task in which they judged whether to let their enterprises settle in an industrial zone when the occupancy rate of the industrial zone was either low or high. The behavioral results showed that participants had a higher acceptance rate in the high occupancy rate condition than in the low one, suggesting the existence of herding tendency in top executives’ business decisions. The ERP results indicated that anticonformity choices induced a larger N2 amplitude than herding choices, demonstrating that participants might experience larger perceived risk and more decision conflict when they processed anticonformity choices. In contrast, we observed that herding choices induced a larger LPP amplitude than anticonformity choices, hinting that participants might experience better evaluation categorization and higher decision confidence when they processed herding choices. Based on these results, this study provides new insights into the neural basis of herding decisions made by top executives in business.

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“…Secara khusus, herding tampaknya didorong terutama oleh ketidakpastian pasar, kondisi pasar yang ekstrem dan periode arus informasi yang tinggi (Arjoon & Bhatnagar, 2017;Bernales et al, 2016;Bhaduri & Mahapatra, 2013;Bouri, Gupta, & Roubaud, 2019;Cajueiro & Tabak, 2009;Dong, Gu, & Han, 2010;Indārs et al, 2019;Lan, 2014;Lao & Singh, 2011;Lindhe, 2012;Vo & Phan, 2016). Investor cenderung melakukan herding lebih dekat ketika mereka menghadapi risiko volatilitas tinggi (Al-Shboul, 2012;Balcilar et al, 2013;Bernales et al, 2016;Humayun Kabir & Shakur, 2018;Vo & Phan, 2016). Herding menjadi semakin kuat saat kita bergerak ke arah saham yang lebih kecil (Arjoon & Bhatnagar, 2017;Guney et al, 2017;M.…”

Section: Hasil Dan Pembahasanunclassified

Perilaku Herding Di Pasar Saham: Sebuah Kajian Literatur

Ningtyas

2020

JBME

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Abstrack : This article aims to prove the existence of herding behavior in a number of stock markets in various parts of the world and find out the factors that cause herding behavior. The method used in this article is a research library by taking data from 80 international journals and 4 local journals. The results of our analysis conclude that herding behavior occurs in almost all stock markets in the world. Factors that cause herding behavior include negative news sentiments towards stocks, incentives and career concerns owned by analysts, market risk and firm level uncertainty, market uncertainty, extreme market conditions, periods of high information flow, risk of volatility, analysis of more types of stocks small, economic / financial crisis, declining market conditions, rising interest rates, currency depreciation, poor information environment, and low quality disclosures. The limitation of this article is that the amount of data taken from the results of research in several stock markets is uneven, such as the lack of data retrieval from the stock market on the American continent Abstrak : Artikel ini bertujuan untuk membuktikan keberadaan perilaku herding di sejumlah pasar saham di berbagai belahan dunia dan mengetahui faktor-faktor penyebab perilaku herding. Metode yang digunakan dalam artikel ini adalah perpustakaan penelitian dengan mengambil data dari 80 jurnal internasional dan 4 jurnal lokal. Hasil analisis kami menyimpulkan bahwa perilaku herding terjadi di hampir semua pasar saham di dunia. Faktor-faktor yang menyebabkan perilaku herding meliputi sentimen berita negatif terhadap saham, insentif dan kekhawatiran karier yang dimiliki oleh analis, risiko pasar dan ketidakpastian tingkat perusahaan, ketidakpastian pasar, kondisi pasar ekstrem, periode arus informasi tinggi, risiko volatilitas, analisis jenis saham yang lebih kecil, terjadinya krisis ekonomi/keuangan, kondisi pasar yang menurun, kenaikan suku bunga, depresiasi mata uang, lingkungan informasi yang buruk, dan pengungkapan berkualitas rendah. Keterbatasan artikel ini adalah jumlah data yang diambil dari hasil penelitian di beberapa pasar saham tidak merata, seperti kurangnya pengambilan data dari pasar saham di benua Amerika.

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Regime-dependent herding behavior in Asian and Latin American stock markets

Cited by 54 publications

References 68 publications

Islamic, Green, and Conventional Cryptocurrency Market Efficiency During the Covid-19 Pandemic

Islamic, Green, and Conventional Cryptocurrency Market Efficiency During the Covid-19 Pandemic

The Neural Basis of Herding Decisions in Enterprise Clustering: An Event-Related Potential Study

Perilaku Herding Di Pasar Saham: Sebuah Kajian Literatur

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