Search results

1 – 3 of 3
Article
Publication date: 9 October 2020

Vijay Kumar Shrotryia and Himanshi Kalra

The present study looks into the mimicking behaviour in both normal and asymmetric scenarios. It, then, considers the contagion between the USA and the BRICS stock markets…

Abstract

Purpose

The present study looks into the mimicking behaviour in both normal and asymmetric scenarios. It, then, considers the contagion between the USA and the BRICS stock markets. Finally, it examines herd behaviour in the wake of a major banking policy change concerning the bloc under study.

Design/methodology/approach

The current empirical analysis employs daily, weekly and monthly data points to estimate relevant herding parameters. Quantile regression specifications of Chang et al. (2000)'s dispersion method have been applied to detect herd activity. Also, dummy regression specifications have been used to examine the impact of various crises and strategically crucial events on the propensity to herd in the BRICS markets. The time period under consideration ranges from January 2011 until May 2019.

Findings

The relevant herding coefficients turn insignificant in most cases for normal and asymmetric scenarios except for China and South Africa. This can be traced to the anti-herding behaviour of investors, where individuals tend to diverge from the consensus. However, turbulence makes all stock markets to show some collective trading except Russia. Further, the Chinese stock market seems immune to the frictions in the US stock market. Finally, the Indian and South African markets witness significant herding during the formation of a common depository institution.

Practical implications

Most stock markets seem to herd during turbulence. This revelation is of strategic importance to the regulators and capital market managers. They have to be cautious during crises periods as the illusion of being secured with the masses ends up creating unprecedented frictions in the financial markets.

Originality/value

The present study seems to be the very first attempt to test the relevant distributions' tails for convergent behaviour in the BRICS markets.

Details

Review of Behavioral Finance, vol. 14 no. 1
Type: Research Article
ISSN: 1940-5979

Keywords

Article
Publication date: 22 March 2021

Vijay Kumar Shrotryia and Himanshi Kalra

With 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…

1209

Abstract

Purpose

With 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/approach

The 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.

Findings

The 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 implications

Drawing 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/value

The 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).

Details

Review of Behavioral Finance, vol. 14 no. 5
Type: Research Article
ISSN: 1940-5979

Keywords

Article
Publication date: 13 May 2021

Vijay Kumar Shrotryia and Himanshi Kalra

The main purpose of the present study is to delve into the overconfidence bias in global stock markets during both pre COVID-19 and COVID-19 phases.

Abstract

Purpose

The main purpose of the present study is to delve into the overconfidence bias in global stock markets during both pre COVID-19 and COVID-19 phases.

Design/methodology/approach

The present study makes use of daily adjusted closing prices and volume of the broad market indices of 46 global stock markets over a period ranging from July 2015 till June 2020. The sample period is split into pre COVID-19 and COVID-19 phases. In order to test the overconfidence fallacy in the chosen stock markets, bivariate market-wide vector auto regression (VAR) models and impulse response functions (IRFs) have been employed in both phases.

Findings

A highly significant contemporaneous relationship between market return and volume appears to be more pronounced in the Japanese, US, Chinese and Vietnamese stock markets in the pre COVID-19 era for the relevant coefficients are positive and highly significant for most lags. Coming to the period of turbulence, the present study discovers strong overconfident behavior in the Chinese, Taiwanese, Turkish, Jordanian and Vietnamese stock markets during COVID-19 phase.

Practical implications

A stark finding is that none of the developed stock markets reveal strong overconfidence bias during pandemic, suggesting a loss or decline in the investors' confidence. Therefore, the regulators should try to regain the investors' trust and confidence in the markets by ensuring honest, fair and transparent practices. The money managers should reduce the transaction cost to encourage trading and educate investors to hold a well-diversified portfolio to mitigate risk in the long run. The governments may launch recovery packages focusing on sustaining and improving economic activities. Finally, a better investment culture may be built by the corporate houses through good corporate governance practices to regain lost trust.

Originality/value

The present study appears to be the very first attempt to gauge overconfidence bias in the wake of a recent COVID-19 pandemic.

Details

International Journal of Emerging Markets, vol. 18 no. 3
Type: Research Article
ISSN: 1746-8809

Keywords

1 – 3 of 3