Volume-herding interaction in the American market

BenSaïda, Ahmed; Jlassi, Mouna; Litimi, Houda

doi:10.1504/ajfa.2015.067837

Cited by 24 publications

(25 citation statements)

References 53 publications

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“…The presence of herding at sectors level was also concluded by Cakan, and Balagyozyan (2016) who found evidence of herding in all sectors of Turkish market and BenSaï da (2017) who detected herding in 10 out of 12 sectors in the U.S market. In addition, the results of this study revealed that the existence of herding at market level is not different before and after the global financial crisis (it was absent during both periods) which is the same conclusion reached by Al-Shboul (2012a) and opposite to the conclusions of Angela-Maria, Maria, and Miruna (2015) and BenSaï da, Jlassi, and Litimi (2015) who claimed that the global financial crisis affected the herding behavior among investors.…”

Section: Discussionsupporting

confidence: 72%

“…Many studies, however, claimed that herding is not constant but it's changing over time as reported by Sharma et al (2015) and Curto, Falcã o, and Braga (2017). In addition, the level of herding behavior was found to be changing based on the market conditions of rising and falling (Chiang et al, 2013;Erdenetsogt & Kallinterakis, 2016;Rahman et al, 2015) and before and during the global financial crisis (Al-Shboul, 2012a; BenSaï da, Jlassi & Litimi, 2015). In the Jordanian market, where few studies about herding were conducted, the presence of herding was evidenced by Obaidat (2016), Ramadan (2015), and Nasarudin, Noordin, Law, and Yahya (2017) while no evidence of herding was found by Al-Shboul (2012a) in both conditions of market rising and falling.…”

Section: Evidence Of Herdingmentioning

confidence: 99%

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Testing Sectoral Herding in the Jordanian Stock Market

Elshqirat¹

2019

IBR

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The main purposes of this quantitative study were to examine the existence of herding behavior among investors in Amman stock exchange (ASE) at market and sector level in addition to testing the behavior during the market rising and falling and examining whether the behavior existence is different before and after the global financial crisis of 2008. The theoretical base of the study was the behavioral finance which assumes that investors are not completely rational and they may follow others when taking investment decisions. The main enquires of the study were about the existence of herding in the Jordanian market, whether it's affected by conditions of market rising and falling, and whether it's affected by the financial crisis. A quantitative design was employed to achieve the purposes of this study which covers the period 2000 - 2018. Data were obtained from ASE website and analyzed using ordinary least squares method. The results indicated that herding is absent in the Jordanian market if tested at market level while it exists in services and industrial sectors if tested at sectors level. The financial crisis did not affect the presence of herding at market level while it did affect the behavior in services and industrial sectors. Moreover, the results revealed that market condition of rising and falling affected herding at market level but not at sectors level. It is also concluded that the global financial crisis changed the presence of herding behavior during conditions of rising and falling in market and in each sector.

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Section: Discussionsupporting

confidence: 72%

Section: Evidence Of Herdingmentioning

confidence: 99%

Testing Sectoral Herding in the Jordanian Stock Market

Elshqirat¹

2019

IBR

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“…More specifically, to investigate the presence of herding behaviour in upward trends and downward trends, further, we divided the whole data into three panels, that is, panel A presents the whole period, panel B presents before the COVID-19 outbreak period and panel C presents after the COVID-19 outbreak period. The normality test shows that all series of market return and CSAD are not normal since their skewness terms are different from 0, and their kurtosis coefficients largely exceed 3 (BenSaïda et al, 2015). Moreover, the CSAD t series are stationary but non-normal and asymmetrical, since their kurtosis largely exceeds the threshold.…”

Section: Resultsmentioning

confidence: 99%

“…In the finance literature, behavioural aspect in investment decision has always been a debatable topic for investors, financial asset managers as well as academic researchers (BenSaïda et al, 2015; Chauhan et al, 2019). Behavioural finance suggests that investors mimic others’ action, especially during the turbulent period of fear, uncertainty and panic.…”

Section: Introductionmentioning

confidence: 99%

The COVID-19 Pandemic and Herding Behaviour: Evidence from India’s Stock Market

Dhall

Singh

2020

Millennial Asia

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This article examines the herding behaviour at the industry level from national stock exchange (NSE). The novel contribution of this article is to examine the herding behaviour during the whole, pre- and post-coronavirus disease 2019 (COVID-19) pandemic outbreak period. We deployed the popular model proposed by Chang et al. (2000) to examine herd formation. Using daily stock closing prices of 191 firms, which constitute the 12 industry indices for the period from 1 January 2015 to 1 June 2020, the results for the full sample period (1 January 2015 to 1 June 2020) and before COVID-19 outbreak period (1 January 2015 to 29 January 2020) indicate the non-existence of herding formation at the industry level, but they do suggest a strong evidence of anti-herding behaviour. In addition, during the bull and bear market conditions, we found evidence of herding behaviour during the post-COVID-19 outbreak period (1 January 2020 to 1 June 2020). Further, the findings suggest that COVID-19 pandemic caused the formation of herding behaviour at the industry level. The study facilitates investors to devise their trading strategies in the regime of the COVID-19 pandemic.

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“…For example, the banking network structure is not a random network; relevant studies show that banking networks have significant scale-free network characteristics [37]. The investment of banks is not completely random, and there may be herd effect [38]. However, the model in this paper can well reflect the risk of the banking system.…”

Section: Conclusion and Discussionmentioning

confidence: 96%

Systemic Risk in the Interbank Market with Overlapping Portfolios

Jiang

Fan

2019

Complexity

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The increasing frequency and scope of the financial crisis have attracted more attention in the research of the systemic risk of banking system. A new model for the interbank market with overlapping portfolios is proposed to simulate a banking system in this work. The proposed model uses a bipartite network of banks and their assets to analyze the impact of bank investment on the stability of the banking system. In addition, this model introduces investment risk and allows banks to make up for liquidity by selling devaluated assets, which reflects the operating rules of the banking system more realistically. The results show that allowing banks to sell devaluated assets to make up for liquidity can improve the stability of the banking system and the interbank market can also improve the stability of the banking system. For the investment of banks, the investment risk is an uncertain factor that affects the stability of the banking system. The proposed model further analyzes the impact of average investment interest rate, savings interest rate, deposit reserve ratio, and investment asset diversity on the stability of the banking system. The model provides a tool for policy-makers and supervision agencies to prevent the systemic risk of banking system.

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Volume-herding interaction in the American market

Cited by 24 publications

References 53 publications

Testing Sectoral Herding in the Jordanian Stock Market

Testing Sectoral Herding in the Jordanian Stock Market

The COVID-19 Pandemic and Herding Behaviour: Evidence from India’s Stock Market

Systemic Risk in the Interbank Market with Overlapping Portfolios

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