Herding and excessive risk in the American stock market: A sectoral analysis

Litimi, Houda; BenSaïda, Ahmed; Bouraoui, Omar

doi:10.1016/j.ribaf.2016.03.008

Cited by 94 publications

(81 citation statements)

References 43 publications

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“…The sample period ranges from January 2003 to December 2016. In particular, the global financial crisis periods is identified as 03 May 2008 -31 May 2009 by following Chiang and Zheng (2010) and Litimi et al (2016).…”

Section: Methodsmentioning

confidence: 99%

“…It relates to ignoring the private information and beliefs of an investor by joining collectively in trade of group, even the trade is not supported by valid information. The investors may only imitate and follow the action of a peer of investors (Litimi et al, 2016). Such imitation or herd originates from the habit of animals and has been documented among birds, fish, and mammals in foraging and diet choices (Hirshleifer & Teoh, 2003).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Therefore, Chang et al (2000) propose a more robust proxy of herding inspired by CAPM, that is cross-sectional absolute deviation of returns (CSAD). The formula of CSAD is expressed as follows: (11) Where CSAD is a measure of returns dispersion; Ri,t is the realized returns on stock i on time t; Rm,t is the average value of an equally weighted realized returns of all stock in portfolio at time t. Litimi et al (2016) suggest that the measure of CSAD is a proxy for herding, but it does not mean the presence of herding itself. CSAD is the average of the proximity of the individual returns to the average market return.…”

Section: Applying An International Capm To Herding Behaviour Model Fomentioning

confidence: 99%

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Applying an international CAPM to herding behaviour model for integrated stock markets

Najmudin

Syarif

Wahyudi

et al. 2017

Journal of International Studies

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Abstract. Development of financial globalization in the form of stock market integration experiences a trend which is getting stronger. The analysis models in the field of finance and investments should be able to adjust to these developments. This adjustment includes the models used to detect the existence of herding behavior. All this time, the herding behavior model of individual stocks towards market consensus has been referring to CAPM theory. The basic assumption of CAPM is that financial assets at a domestic stock market are segmented from the financial assets' movement at the global market. Therefore, this paper aims to provide an alternative view in the form of an international herding model that should be applied in the context of an integrated stock market. The model was created with reference to the international CAPM. This paper combined ICAPM method and international CSAD model to identify herding for eight stock markets, the sample period being from January 2003 to December 2016. The result found that for segmented stock markets, represented by China Vol.10, No.4, 2017 48 and the Philippines, herding happened for both overall the sample period and the market crisis period. In addition, for the integrated stock markets, represented by Indonesia, Japan, Malaysia, Singapore, Thailand, and the UK, herding behavior was only found during the market crisis period. Therefore, classification of market integrations should be considered in assessing the herding behaviour at stock markets.

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Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Applying An International Capm To Herding Behaviour Model Fomentioning

confidence: 99%

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Applying an international CAPM to herding behaviour model for integrated stock markets

Najmudin

Syarif

Wahyudi

et al. 2017

Journal of International Studies

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“…The literature shows that herding is more intensive when the markets are on the uptrend (see, e.g., Ouarda et al, 2013;Litimi et al, 2016;BenSaïda 2017). A dummy variable D t up is introduced at time t , which takes the value 1 for all positive observations during the sampling period, or zero otherwise.…”

Section: Econometric Frameworkmentioning

confidence: 99%

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

Senarathne¹,

Jiang²

2020

EurJ Appl Econ

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This paper sets out to explore whether the investor herding in the cryptocurrency market induces correlations in cryptocurrency returns using the methodology of Chang et al. (2000) and Galariotis et al. (2015) from a daily data sampling period of 3/30/2015 to 5/24/2019. The initial regression results show that the cross-sectional absolute deviation of return can only be explained by GSCI oil and gold index return, but no relationship exists between cross-sectional absolute deviation of return and other regression variables, such as return on CCi30, US equity risk premium and US/Euro exchange rate return. The herding regression results under normal market condition show that a strong tendency exists to herd on non-fundamental information that explains cross-sectional absolute deviation of returns. As such, cryptocurrency returns cannot be predicted on the basis of fundamental economic information (e.g., major macroeconomic announcements). Herding on non-fundamental information is found to be more pronounced during an upward-trending period of the market and other than upward-trending period. No signs of herding on fundamental information could be observed under other market conditions. Although the theory suggests that herding on non-fundamental information results in more efficient outcomes, the above findings do not encourage the diversification of traditional assets with cryptocurrency on the basis of low correlation. Since cryptocurrency lacks intrinsic value, the exchange is shown to provide a pseudo-efficient trading platform for speculative investors. Implications for future research are discussed.

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“…Badhani stocks and thereafter followed by other investors as a results trading volume of those specific stocks about which information were available face abnormally high trading volume resulted in high volatility in these stocks. If the market is enough large, overall volatility comes down[41]. Thus herding behaviour positively affects the volatility of some specific share while negatively affect the over-…”

mentioning

confidence: 99%

Empirical Investigation of Herding under Different Economic Setups

Kumar¹,

Badhani²

2018

TEL

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Present study is an attempt to analyse the presence of herding in different economic conditions. A mix of developed and developing countries is selected from different corners of the word. Our sample comprises 35 world markets, out of which 18 are emerging markets while 17 are developed markets. Daily data of all constituents stocks of the representative indices of these markets are extracted over most recent period ranging from Jan. 2000 to Apr. 2018. Applying different methodologies static and time varying, we find that only 11 markets out of 35 exhibit significant herding behaviour. These markets majorly belong to Asia, Africa and Middle East. We also try to relate herding with region, culture and state of economy and do not find any significant relation of these variables with herding.

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Herding and excessive risk in the American stock market: A sectoral analysis

Cited by 94 publications

References 43 publications

Applying an international CAPM to herding behaviour model for integrated stock markets

Applying an international CAPM to herding behaviour model for integrated stock markets

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

Empirical Investigation of Herding under Different Economic Setups

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