scholarly journals Herd behaviour as a source of volatility in agent expectations

2006 ◽  
Author(s):  
M. Bowden ◽  
S. McDonald
Keyword(s):  
Herd Behaviour

Herd Behaviour: How Decisive is the Noise in the NSE and BSE Stock Markets?

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Paritosh Chandra Sinha
Keyword(s):  
Behavioral Finance ◽  
Stock Markets ◽  
High Frequency ◽  
Stock Exchange ◽  
Time Stamp ◽  
Trade Volume ◽  
Herding Behavior ◽  
Equilibrium Pricing ◽  
Indian Context ◽  
Herd Behaviour

Do investors in the stock markets act/react on true information or noise? Do they believe on their own information or simply herd? The study seeks to explore these typical research queries from the behavioral finance perspectives. In particular, it develops a new theory of herding behavior and extends the models of Banerjee (1992) and Bikhchandani, Hirshleifer, and Welch (1992). The study also empirically tests the same on the Indian context with the high frequency intraday trading data for the real trade-time or time-stamp, trade-volume, and trade-price of ten sample scripts listed for their trading in both markets - the Bombay Stock Exchange (BSE) and the National stock Exchange (NSE). The study contributes to the literature with original findings. It shows that investors in the two Indian stock markets show crowd of positive and negative herding as well significantly and there is huge noise along with information in the markets equilibrium pricing mechanism.

scholarly journals INVESTOR HERD BEHAVIOUR IN AFRICA’S EMERGING AND FRONTIER MARKETS

2020 ◽  
Vol 10 (6) ◽  
pp. 194-205
Author(s):  
Godfred Aawaar ◽  
Nicholas Addai Boamah ◽  
Joseph Oscar Akotey
Keyword(s):  
Herd Behaviour

Herd Behaviour in Adoption of Network Technologies

2005 ◽  
Vol 86 (2) ◽  
pp. 161-182 ◽  
Author(s):  
Cecilia Vergari
Keyword(s):  
Herd Behaviour ◽  
Network Technologies

scholarly journals Solving the Mystery of Crypto’s Bubble

2020 ◽  
Vol 19 (3) ◽  
pp. 25-39
Author(s):  
Harsh Sengar
Keyword(s):  
Legal Entity ◽  
Market Participants ◽  
True Value ◽  
Herd Behaviour ◽  
Rational Bubble ◽  
Adf Test

Blockchain is the vehicle on which cryptocurrencies run, and it can’t be regulated by any legal entity during its operation.The huge growth in various cryptocurrency segments in 10 years has created the controversy of an inevitable bubble. A bubble can be generated either by queer herd behaviour or logical secular movement. Traces of evident bubbles have been a certainty and they take the perceived valuation of crypto to figures far away from its true value. This sudden diversion can be lethal due to the illogical, irrational propensity of regular market participants. This study observes ten cryptos under surveillance from September 2014 to August 2019. The selected ten (Monero, Bitcoin, XRP Ripple, Litecoin, Dogecoin, Monacoin, Ethereum, Bytecoin, Digibite, Potcoin) cryptocurrencies were studied for the last five years using Right Tailed ADF Test. Prominent traces of the rational bubble in all the underlying cryptocurrencies were found and have been considered for the study.

An Examination of Herd Behaviour: Evidence from Colombo Stock Exchange

2020 ◽  
Author(s):  
S. M Abeysekera ◽  
D. C. Wijesinghe ◽  
S. S. Weligamage
Keyword(s):  
Stock Exchange ◽  
Herd Behaviour

scholarly journals Herd behaviour & investor sentiment: Evidence from UK mutual funds

2020 ◽  
Vol 71 ◽  
pp. 101494 ◽  
Author(s):  
Yawen Hudson ◽  
Meilan Yan ◽  
Dalu Zhang
Keyword(s):  
Mutual Funds ◽  
Investor Sentiment ◽  
Herd Behaviour

Herding behavior in Islamic GCC stock market: a daily analysis

2018 ◽  
Vol 11 (2) ◽  
pp. 182-193 ◽  
Author(s):  
Mustapha Chaffai ◽  
Imed Medhioub
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Financial Markets ◽  
Stock Returns ◽  
Stock Markets ◽  
Content Type ◽  
Quantile Regression Analysis ◽  
Herd Behaviour ◽  
The Impact ◽  
Quantile Regression Method

Purpose This paper aims to examine the presence of herd behaviour in the Islamic Gulf Cooperation Council (GCC) stock markets following the methodology given by Chiang and Zheng (2010). Generalized auto regressive conditional heteroskedasticity (GARCH)-type models and quantile regression analysis are used and applied to daily data ranging from 3 January 2010 to 28 July 2016. Results show evidence of herd behaviour in the GCC stock markets. When the data are divided into down and up market periods, herd information is found to be statistically significant and negative during upward market periods only. These results are similar to those reported in some emerging markets such as China, Japan and Hong Kong, where stock returns perform more similarly during down market periods and differently during rising markets. Design/methodology/approach The authors present a brief literature on herd behaviour. Second, the authors provide some specificity of the GCC Islamic stock market, followed by the presentation of the methodology and the data, results and their interpretation. Findings The authors take into account the difference existing in market conditions and find evidence of herding behaviour during rising markets only for GCC markets. This result was confirmed after using the quantile regression method, as evidence of herding was observed only in highly extreme periods. Stock returns perform more similarly when market is down in Islamic GCC stock market. Research limitations/implications The research limitation consists in the fact that this work can be extended to compare the GCC stock markets with other markets in Asia such as Malaysia and Indonesia. Practical implications The principal implication consists in the fact that herding behaviour is limited in the GCC markets and Islamic finance can have an important contribution to moderate the behaviour in the financial markets. Social implications The work focusses on the role of ethics in the financial markets and their ability to reduce the impact of behavioural biases. Originality/value The paper studies the behaviour of investors in the Islamic financial markets and gives an idea about the importance of the behaviour in this particular market regarding its characteristics.

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