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Journal articles on the topic 'Herding'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 July 2024

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1

Ramli, Ishak, Sukrisno Agoes, and Ignatius Roni Setyawan. "Information Asymmetry And The Role Of Foreign Investors In Daily Transactions During The Crisis; A Study Of Herding In The Indonesian Stock Exchange." Journal of Applied Business Research (JABR) 32, no. 1 (June 25, 2016): 269–88. http://dx.doi.org/10.19030/jabr.v32i1.10178.

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The purpose of this study is to prove that there was herding behavior by domestic investors following that of foreign investors in the Indonesian Capital Market (IDX) and that the herding was influenced by information asymmetry. It began when global investors undertook international diversification to the IDX because the returns on their portfolios were not on the efficient frontier during the crisis and because of the low correlation between Indonesia’s economy and the American and European economies. Utilizing the IDX daily transaction data during the years 2009-2011, the herding behavior of domestic investors, which followed that of foreign investors, was tested by Lakonishok models as was the influence of information asymmetry on the herding. It was found that the herding behavior in the IDX occurred in buy, sell or entire herdings (buy and sell). There were 0.40 to 0.55 buy herdings and 0.20 to 0.40 sell herdings during the crisis in 2008 and 2009. Buy herding then continued in 2010 onwards, although with lower intensity (0.05 to 0.20); however, sell herding decreased dramatically, and there has been almost no sell herding since then. Nevertheless, domestic investors did then sell in the opposite strategy, which was to sell when foreign investors tended to buy. Subsequent findings demonstrated that herding occurred with the influence of information asymmetry between domestic and foreign investors.
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Ramli, Ishak, Sukrisno Agoes, and Ignatius Roni Setyawan. "Information Asymmetry And The Role Of Foreign Investors In Daily Transactions During The Crisis; A Study Of Herding In The Indonesian Stock Exchange." Journal of Applied Business Research (JABR) 32, no. 1 (December 31, 2015): 269. http://dx.doi.org/10.19030/jabr.v32i1.9537.

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<p>The purpose of this study is to prove that there was herding behavior by domestic investors following that of foreign investors in the Indonesian Capital Market (IDX) and that the herding was influenced by information asymmetry. It began when global investors undertook international diversification to the IDX because the returns on their portfolios were not on the efficient frontier during the crisis and because of the low correlation between Indonesia’s economy and the American and European economies. Utilizing the IDX daily transaction data during the years 2009-2011, the herding behavior of domestic investors, which followed that of foreign investors, was tested by Lakonishok models as was the influence of information asymmetry on the herding. It was found that the herding behavior in the IDX occurred in buy, sell or entire herdings (buy and sell). There were 0.40 to 0.55 buy herdings and 0.20 to 0.40 sell herdings during the crisis in 2008 and 2009. Buy herding then continued in 2010 onwards, although with lower intensity (0.05 to 0.20); however, sell herding decreased dramatically, and there has been almost no sell herding since then. Nevertheless, domestic investors did then sell in the opposite strategy, which was to sell when foreign investors tended to buy. Subsequent findings demonstrated that herding occurred with the influence of information asymmetry between domestic and foreign investors. </p>
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3

Ristianawati, Yuyun, Prihasantyo Siswo Nugroho, and Kiswoyo. "Pengembangan Kawasan Wisata pada Rest Area Boja dalam Mendukung Peningkatan Pedapatan Desa Melalui Perilaku Herding (Studi Kasus di Kawasan Wisata Rest Area Desa Boja, Kecamatan Boja, Kabupaten Kendal)." Jurnal Ekonomi dan Statistik Indonesia 1, no. 3 (December 29, 2021): 268–75. http://dx.doi.org/10.11594/10.11594/jesi.01.03.12.

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The aims of this research is to study the mindset of Herding's behavior on the income level of tourism objects through the results of tourism development in the Rest Area of Boja Kendal Village. In this study, 95 people/MSMEs. In this study, the authors used a purposive random sampling technique. The results of this study are herding behavior has a positive and significant effect on the income level of MSMEs in the Boja rest area tourist attraction. Herding behavior has no effect on tourism development decisions. The development of tourism objects has no effect on increasing income. Herding behavior has no significant effect on the income level of tourist objects through tourism area development decisions. So that the development of tourist areas is not able to mediate the influence of herding behavior on increasing MSME income in the Boja rest area tourist attraction.
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Ristianawati, Yuyun, Prihasantyo Siswo Nugroho, and Kiswoyo. "Pengembangan Kawasan Wisata pada Rest Area Boja dalam Mendukung Peningkatan Pedapatan Desa Melalui Perilaku Herding (Studi Kasus di Kawasan Wisata Rest Area Desa Boja, Kecamatan Boja, Kabupaten Kendal)." Jurnal Ekonomi dan Statistik Indonesia 1, no. 3 (December 29, 2021): 268–75. http://dx.doi.org/10.11594/jesi.01.03.12.

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The aims of this research is to study the mindset of Herding's behavior on the income level of tourism objects through the results of tourism development in the Rest Area of Boja Kendal Village. In this study, 95 people/MSMEs. In this study, the authors used a purposive random sampling technique. The results of this study are herding behavior has a positive and significant effect on the income level of MSMEs in the Boja rest area tourist attraction. Herding behavior has no effect on tourism development decisions. The development of tourism objects has no effect on increasing income. Herding behavior has no significant effect on the income level of tourist objects through tourism area development decisions. So that the development of tourist areas is not able to mediate the influence of herding behavior on increasing MSME income in the Boja rest area tourist attraction.
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5

Carbone, Enrica. "Ownership herding and informational herding." Applied Economics Letters 17, no. 12 (July 27, 2010): 1201–4. http://dx.doi.org/10.1080/00036840902845392.

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6

Nicol, Danny. "Progressive Eras, Periods of Reaction, and Constitutional Change." German Law Journal 15, no. 3 (May 1, 2014): 437–59. http://dx.doi.org/10.1017/s2071832200018988.

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This article argues that “political herding” plays a crucial role in driving and shaping constitutional change. It links the prevalence of political herding to a psychological phenomenon, “social influence.” It goes on to argue that constitutional change is often driven by the desire for certain substantive policies, which in turn are determined by whether, in a particular epoch, the political community is herding in a progressive or reactionary direction. Contending that the general phenomenon whereby political communities go through recurrent swings to the left or to the right has been neglected by scholars, this essay aims to give this phenomenon the centrality it merits in relation to the evolution of the British constitution. Accordingly it considers the 1906 Liberal government, the 1945 Labour government and the lengthy succession of post-1979 neoliberal governments, analyzing how substantive progressive and reactionary programs led to constitutional change. Finally this article considers the legitimacy both of political herding itself, and of political herding's impact on constitutional change.
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7

ALI, MAZHAR, HUMA AMIR, and AAMIR SHAMSI. "Consumer Herding Behavior in Online Buying: A Literature Review." International Review of Management and Business Research 10, no. 1 (March 7, 2021): 345–60. http://dx.doi.org/10.30543/10-1(2021)-30.

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The purpose of this review paper is to present the application of herding behavior in online buying. The simplest description of herding behavior is the imitation of others in making decisions. Online buying platforms have facilitated observing others' buying behavior, thereby increasing possibilities of social influence on our information search, evaluation, and buying. The concept of herding is multi-disciplinary; however, the literature review on herding behavior is mainly grounded in economics and finance. There is little understanding of herding behavior in marketing literature. Therefore, this study covers herding behavior literature through high-quality research papers published from 2000 to 2020 in journals indexed in the social science citation index, science citation index expanded, and emerging source citation index. This paper discusses the conceptualization of herding in online buying, herding situations, information-processing view of herding, measuring herding effect, herding models and theories, and areas for future research to enrich herding literature in online buying. This paper proposes a herding model (HCMMD) based on the stimulus-organism-response (SOR) theory to study herding behavior. Keywords: Consumer Herding Behavior, Herding Literature Review, Herding Models, Online Buying, Stimulus-Organism-Response (SOR) Theory.
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8

Ahmed, Kamran, Khuram Shafi, and Samina Nawab. "DYNAMICS OF HERDING BEHAVIOUR DURING EXTREME MARKET MOVEMENTS IN CHINA AND PAKISTAN." Pakistan Journal of Social Research 04, no. 04 (December 31, 2022): 664–82. http://dx.doi.org/10.52567/pjsr.v4i04.881.

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This paper investigates herding behaviour in China and Pakistan by using dynamic herding approaches and herding during extreme market movements. We use daily returns of the Shanghai stock exchange (SSE) and Pakistan stock exchange (PSX) from 2006 to 2021. Several models are used to study herding, such as least squares model, generalized linear model, and Bai and Perron's structural change model. Overall, results through the linear model show that China has significant herding, but no herding is found in Pakistan. According to Bai and Perron's model, herding is evident in two different regimes of both countries. The first regime shows herding during USA global financial crisis of 2008. The second regime was during the Hong Kong protest, which drove herding in China. In Pakistan, herding is found during political crisis and terrorism activities. From the perspective of extreme market movements, China and Pakistan both showed herding during 10% values. Contrary, no herding was found during 1% values, but Pakistan showed herding during 5% values at both extremes, and China only showed herding during the upper extreme. Hence, herding should be measured at 10% rather than 5% and 1%. Keywords: Behavioural finance, herding behaviour, extreme market movements, cross-sectional absolute deviation, structural change model. Jel classification: G01, G11, G12.
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9

Economou, Fotini. "Herding in frontier markets: evidence from the Balkan region." Review of Behavioral Finance 12, no. 2 (August 12, 2019): 119–35. http://dx.doi.org/10.1108/rbf-08-2018-0090.

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Purpose The purpose of this paper is to examine herding in four frontier markets in the Balkan region, namely, Bulgaria, Croatia, Romania and Slovenia, from October 2000 to December 2016. Design/methodology/approach The author employs Chang et al.’s (2000) cross-sectional dispersion approach to capture herding, while also testing for the global financial crisis’ effects and the European Union (EU)/Euro zone accession effects over herding. Potential asymmetric herding effects conditional on market performance, domestic volatility, German and US investor sentiment are also examined. Finally, the cross-market herding dynamics of the region are also explored. Findings Overall, Romania exhibits the most extensive evidence of herding across various estimations. The empirical results indicate that cross-market herding dynamics within the region generate stronger herding (compared to the herding observed within each stock market individually), suggesting that Balkan stock exchanges’ growing financial integration leads their herding to be “imported”, rather than domestically motivated. Practical implications The findings provide useful insights for regulators in frontier markets, considering the destabilising potential of herding; they are also of particular interest to the investment community for reasons of international asset allocation, diversification and hedging strategies. Originality/value This study contributes to the limited herding literature regarding frontier markets and provides novel findings regarding the herding dynamics in the Balkan region, the EU/Euro zone accession’s effect and global factors’ impact on herding estimations.
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10

Lu, Yang-Cheng, Hao Fang, and Yen-Hsien Lee. "The informational and non-informational compositions of UK fund managers’ dynamic herding in the stock market." Panoeconomicus 64, no. 5 (2017): 571–92. http://dx.doi.org/10.2298/pan150212016l.

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This paper examines whether UK fund managers engage in herding behaviour in the stock market using the dynamic herding measure, whether their herding behaviour is different during bullish and bearish periods, whether most of their herding is informational, which types of informational reasons act as the main drivers of their herding and whether there are non-informational drivers of their herding. Our results reveal that UK fund managers engage in significant herding behaviour and that this behaviour does not differ significantly from bullish to bearish stock markets. Moreover, we confirm that there are weak positive correlations between fund managers? herding and stock returns within the subsequent year, which indicates that their herding is mainly informational. To improve portfolio performance, other investors could follow UK fund managers and purchase stocks overbought by them with at least 15 traders quarterly in the following one-year period, particularly for growth-type, sectorspecific and international-type funds. Moreover, because they are more likely to herd in large-capitalisation securities, the informational reasons driving managers? herding behaviour are mainly related to investigative herding. We also find that growth-type and international-type funds are more likely to herd with similar- type funds. This finding may result from reputational and characteristic herding, which illustrates that non-informational reasons for managers? herding still exist.
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11

Messis, Petros, and Achilleas Zapranis. "Herding behaviour and volatility in the Athens Stock Exchange." Journal of Risk Finance 15, no. 5 (November 21, 2014): 572–90. http://dx.doi.org/10.1108/jrf-04-2014-0054.

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Purpose – This study aims to investigate the existence of herding in the Athens Stock Exchange over the 1995-2010 period and examine its effects on market volatility. Design/methodology/approach – Herding is examined over portfolios formed on beta and size of the selected stocks. The detection of herding has been done using the state space model of Hwang and Salmon (2004). Four volatility measures are employed. Findings – The findings depict the presence of herding over two different periods of time. Large differences are observed among the portfolios regarding the herding periods. The results confirm a linear effect of herding on all volatility measures considered. Stocks exhibiting higher levels of herding or adverse herding will also present higher volatility, and from this point of view, herding can be regarded as an additional risk factor. Originality/value – The fact that herding is considered to be an additional risk factor, can lead market participants and investors to a better understanding of market risk, asset pricing and asset allocation.
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12

Ridgway, Marcella. "Herding Dogs." Veterinary Clinics of North America: Small Animal Practice 51, no. 4 (July 2021): 975–84. http://dx.doi.org/10.1016/j.cvsm.2021.04.013.

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13

Dick, Dennis. "Herding Apples." CFA Institute Magazine 23, no. 3 (May 2012): 40–41. http://dx.doi.org/10.2469/cfm.v23.n3.23.

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Bartosiewicz, László. "Herding Cats." Current Swedish Archaeology 29, no. 1 (December 9, 2021): 56–71. http://dx.doi.org/10.37718/csa.2021.07.

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McKinnon, Ann Marie. "Herding Community." Humanimalia 12, no. 1 (September 10, 2020): 95–117. http://dx.doi.org/10.52537/humanimalia.9425.

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The Icelandic horse in the film Of Horses and Men is an individual understood on the basis of what it does, a biosocial becoming in a specific geography, society, and historical moment. The horse is a film actor and an agent and, seen through the visual repetition of the gaze of the horse in the film, offers a clear example of entangled agencies -- a herd of human and non-human animals -- that co-create their Icelandic home. This creaturely gaze emphasizes the relations between human and animal, undoes the conventional anthropocentric bias of the gaze in cinema, and informs an ethics that relies on the materiality and vulnerability of all living bodies.
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Tyner, James. "Herding elephants." Dialogues in Human Geography 6, no. 2 (July 2016): 190–97. http://dx.doi.org/10.1177/2043820616655030.

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Smith, John R. "Herding Cats." IEEE MultiMedia 20, no. 4 (October 2013): 2–3. http://dx.doi.org/10.1109/mmul.2013.56.

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Alglave, Jade, Luc Maranget, and Michael Tautschnig. "Herding Cats." ACM Transactions on Programming Languages and Systems 36, no. 2 (July 2014): 1–74. http://dx.doi.org/10.1145/2627752.

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Petsko, G. A. "Herding CATS." Science Translational Medicine 3, no. 97 (August 24, 2011): 97cm24. http://dx.doi.org/10.1126/scitranslmed.3002837.

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van Dellen, James R. "“Herding Cats”." World Neurosurgery 116 (August 2018): 451–53. http://dx.doi.org/10.1016/j.wneu.2018.05.250.

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Forrest, ARW. "Herding cats." Science & Justice 42, no. 1 (January 2002): 1–2. http://dx.doi.org/10.1016/s1355-0306(02)71787-5.

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Sias, Richard W. "Institutional Herding." Review of Financial Studies 17, no. 1 (August 11, 2003): 165–206. http://dx.doi.org/10.1093/rfs/hhg035.

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Waugh, Katharine A. "Herding Cats." Internet Reference Services Quarterly 1, no. 4 (January 10, 1997): 7. http://dx.doi.org/10.1300/j136v01n04_03.

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Vellucci, Sherry L. "Herding Cats." Internet Reference Services Quarterly 1, no. 4 (January 10, 1997): 9–30. http://dx.doi.org/10.1300/j136v01n04_04.

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Krevit, Leah, and Linda Crays. "Herding cats." OCLC Systems & Services: International digital library perspectives 23, no. 2 (June 5, 2007): 116–24. http://dx.doi.org/10.1108/1065075071074844.

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Alglave, Jade, Luc Maranget, and Michael Tautschnig. "Herding cats." ACM SIGPLAN Notices 49, no. 6 (June 5, 2014): 40. http://dx.doi.org/10.1145/2666356.2594347.

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Blaivas, Jerry G. "Herding cats." Neurourology and Urodynamics 20, no. 1 (2000): 1. http://dx.doi.org/10.1002/1520-6777(2001)20:1<1::aid-nau1>3.0.co;2-3.

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28

Liu, Yujia, and Liang Wu. "The Asymmetric Effect of Mutual Fund Herding on Price Deviation: Evidence from the Chinese Stock Market." International Journal of Economic Behavior and Organization 12, no. 3 (July 4, 2024): 123–35. http://dx.doi.org/10.11648/j.ijebo.20241203.12.

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Mutual funds, as significant participants in financial markets, play a crucial role in the formation of asset pricing. The relationship between herding behavior of mutual funds and mispricing has been a subject of intense debate among scholars. In this paper, we investigate the asymmetric impact of mutual fund herding on price deviation and explore the underlying mechanism. In terms of research design, this study selects relevant data on mutual fund holdings and stock trading in the Chinese A-share market from 2010 to 2023, we examine whether herding behavior leads to mispricing, specifically focusing on the asymmetric effects of herding buying and herding selling on stock price deviation from intrinsic value. This study distinguishes the trading direction of mutual fund herding behavior and separately examines the relationship between herding buying behavior and herding selling behavior with stock price deviation. Our empirical findings reveal that buying herding behavior is linked to positive price deviations from intrinsic value. However, selling herding behavior shows no significant relationship with price deviation. Furthermore, our results provide evidence that the herding buying of mutual funds stimulates similar trading sentiments among other market participants and contributes to the formation of market bubbles, while herding selling prompts counterbalancing trades, mitigating the impact of price deviation.
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Zhang, Hang, and Evangelos Giouvris. "Measures of Volatility, Crises, Sentiment and the Role of U.S. ‘Fear’ Index (VIX) on Herding in BRICS (2007–2021)." Journal of Risk and Financial Management 15, no. 3 (March 11, 2022): 134. http://dx.doi.org/10.3390/jrfm15030134.

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We look into determinants (volatility, crises, sentiment and the U.S. ‘fear’ index) of herding using BRICS as our sample. Investors herd selectively to crises and herding is a short-lived phenomenon. Herding was highest during the global financial crisis (only China was affected). There was no herding during the European debt crisis and COVID. With regard to the relationship between volatility and CSAD (cross sectional absolute deviation)/herding, a lower CSAD (movement in a specific direction) brings about less volatility. However, a high volatility amplifies herding (reduces CSAD), especially in China. Russia and South Africa are unresponsive to volatility levels (low/high) and herding. We also observe volatility heterogeneity. Different volatility measures have different effects on different markets. There is limited evidence to suggest that sentiment (based on principal component) Granger causes herding/CSAD. Herding is a period and market variant and unrelated to crises. The U.S. ‘fear’ index has a short-lived, limited effect on CSAD/herding (during COVID only) for all countries except China. In addition, Granger causality analysis indicates a two-way relationship between the U.S. ‘fear’ index and CSAD/herding, unrelated to crises.
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Sharma, Susan Sunila, Paresh Narayan, and Kannan Thuraisamy. "Time-Varying Herding Behavior, Global Financial Crisis, and the Chinese Stock Market." Review of Pacific Basin Financial Markets and Policies 18, no. 02 (June 2015): 1550009. http://dx.doi.org/10.1142/s0219091515500095.

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In this paper, we examine the evidence of herding behavior on the Chinese stock market. Our main findings are as follows. First, we find strong evidence of herding behavior on both the Shanghai and Shenzhen stock exchanges. Second, we document evidence of asymmetric herding behavior with greater magnitude of herding behavior on up markets than on down markets. Third, our findings suggest that herding behavior is sector-specific and predominant in the industrial and properties sectors. Finally, we unravel strong evidence suggesting that herding behavior is time-varying and in some sectors time-varying herding behavior is more prevalent than in other sectors.
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Choi, Ki-Hong, and Seong-Min Yoon. "Investor Sentiment and Herding Behavior in the Korean Stock Market." International Journal of Financial Studies 8, no. 2 (June 1, 2020): 34. http://dx.doi.org/10.3390/ijfs8020034.

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This paper investigates herding behavior and the connection between herding behavior and investor sentiment. We apply a Cross-Sectional Absolute Deviation (CSAD) approach and the quantile regression method to capture herding behavior in the KOSPI and KOSDAQ stock markets. The analysis results are outlined as follows. First, we find that herding behavior is exhibited during down-market periods in the KOSPI and KOSDAQ stock markets. However, we show that adverse herding behavior occurs in low-trading volume and low-volatility periods. Second, according to the results of the quantile regression, herding behavior is found in the low and high quantiles of the KOSPI and KOSDAQ stock markets. However, adverse herding behavior is also found, which means that investors herd in extreme market conditions. Third, the relationship between investor sentiment and herding behavior is analyzed through regression and quantile regression, and investor sentiment is confirmed to be one of the important factors that can cause herding behavior in the Korean stock market.
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Wong, Tze Sun. "Stock Characteristics and Individual Herding." International Journal of Applied Behavioral Economics 9, no. 4 (October 2020): 58–73. http://dx.doi.org/10.4018/ijabe.2020100104.

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Individuals who invest stocks in a market with excess volatility generally end up selling or holding the stocks at losses. The purpose of this study was to examine individual herding as it related to three comprehensible stock characteristics, market capitalization, price-to-book ratio, and industry affiliation. The target population was the individual investors who traded in Taiwan Stock Exchange in 2016. Data were collected through subscription. Based on Lakonishok, Shleifer, and Vishny's measure, individual herding was significant. The three stock characteristics were separately and as a whole related to individual herding. The findings confirmed sell-herding higher than buy-herding, more serious herding in high market capitalization stocks, and broad industry herding. The findings also extended knowledge to comparable herding levels with 8 to 10 years ago, more linearity between log market capitalization and log odds of herd occurrence, and less herding in P/B ratio stocks with other independent variables controlled.
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R., Ganesh, Naresh Gopal, and Thiyagarajan S. "Bulk and block holders herding behaviour." South Asian Journal of Business Studies 7, no. 2 (June 4, 2018): 150–71. http://dx.doi.org/10.1108/sajbs-12-2017-0139.

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Purpose The purpose of this paper is to examine industry herding among the institutional investors and to find whether their herding behaviour is intentional or unintentional. Design/methodology/approach The study uses Lakonishok et al. (1992) model to examine the presence of industry herding behaviour among institutional investors. To determine whether the herding observed is intentional or unintentional, herding measure is regressed with volatility, volume, beta and return. The period of the study is from 1 April 2005-31 March 2015. Findings The findings of the study showed that though institutional investors have herding tendency towards most of the industries, in the overall period industry herding was not significant. The herding found in some industrial sectors was linked to economic performance of those sectors in India during the period of study and hence the herding was unintentional in nature. Research limitations/implications This is the first attempt to study industry herding among institutional investors and their intent in Indian market ever since the country opened its market to foreign investors in a big way. Present study is limited to the use of only bulk/block data instead of the entire trading data for the period. Originality/value This study is the first attempt to investigate industry herding behaviour of institutional investors in the market using their bulk and block trading data. The herding observed in well performing industries has been shown to be unintentional and hence rational. The results indicate that the entry of big institutional investors, including foreign institutions into the Indian market has not destabilised the market by irrational herding.
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R., Ganesh, Naresh G., and Thiyagarajan S. "Mimicking behaviour in bulk and block trading of institutional investors in the stock market." Benchmarking: An International Journal 25, no. 7 (October 1, 2018): 2414–26. http://dx.doi.org/10.1108/bij-04-2017-0063.

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PurposeThe purpose of this paper is to examine the mimicking behaviour of institutional investors in the stock market.Design/methodology/approachThe study focusses on examining the herding behaviour among institutional investors in the stock market by considering the bulk and block trade on the constituent NIFTY 50 index during the period 2005–2015 using Lakonishok–Schleifer–Vishny (1992) model. The study also aims to find out whether their herding behaviour is intentional or unintentional in nature.FindingsThe findings of the study showed no sign of herding behaviour in the market; out of 50 constituent stocks of NIFTY 50, there was significant herding in 15 stocks, with buy herding in 11 stocks and sell herding in four stocks, and remaining 35 stocks were totally free from herding behaviour. In addition, the results proved that the herding behaviour observed on the stocks is of unintentional in nature.Research limitations/implicationsPresent study is limited to the use of constituent stocks of the Benchmarking Index NIFTY 50.Originality/valueThis study is the first attempt to investigate the herding behaviour of institutional investors in the market using bulk and block trade and also to explore their intent in herding behaviour.
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Gusni, Gusni, Nugraha Nugraha, Disman Disman, and Tomas Chochole. "Analysis of Aggregate Herding Behavior in the Capital Market: Evidence from Indonesia and Singapore." Media Ekonomi dan Manajemen 38, no. 2 (July 28, 2023): 362. http://dx.doi.org/10.56444/mem.v38i2.3934.

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<p>The high uncertainty in the capital market due to some crises that hit the world over the last few decades has the potential to cause herding behavior in the aggregate capital market, both in developed and emerging capital markets. The main objective of this study is to detect the existence of herding behavior, including asymmetric herding and global factor drives (oil prices and fed fund rates) on aggregate herding behavior in the Indonesian and Singapore capital markets during the period Jan 2015 to December 2020. This study employs a cross-sectional dispersion approach to achieve study goals. Research findings denote aggregate herding behavior occurs only in the Singapore capital market, while in Indonesia no herding behavior is detected. Asymmetric herding testing for both capital markets revealed no herding tendency in up and down market conditions. This condition implies that low volatility cannot ensure the absence of aggregate herding behavior. Global factors have proven to significantly drive herding behavior in the Singapore capital market, while in Indonesia it is only the oil price. The findings of this study will provide information that policymakers can use to maintain capital market stability in both countries.</p>
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Mertzanis, Charilaos, and Noha Allam. "Political Instability and Herding Behaviour: Evidence from Egypt’s Stock Market." Journal of Emerging Market Finance 17, no. 1 (February 23, 2018): 29–59. http://dx.doi.org/10.1177/0972652717748087.

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This article examines the existence of herding behaviour in the Egyptian stock market during the 2011 revolution period. Using daily and monthly data, we test for the existence of herding for the whole period, as well as for the pre- and post-revolution phases. For the whole period, our results fail to provide evidence of herding behaviour in the Egyptian stock market, but do provide evidence of adverse herding behaviour that exhibits non-linearity. The results also fail to provide evidence of herding behaviour during bull and bear markets, and show that herding behaviour is a short-lived phenomenon. When the pre- and post-revolution phases are considered separately, the results provide evidence of weak adverse herding for both phases and of adverse herding in bullish markets, but they are inconclusive regarding bearish markets. JEL Classification: G10, G15
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37

Hidayati, Lina Nur, Muniya Alteza, and Winarno Winarno. "Herding Behavior: Intensification and Flow in the Indonesian Stock Market." Economic and Regional Studies / Studia Ekonomiczne i Regionalne 15, no. 3 (September 1, 2022): 351–67. http://dx.doi.org/10.2478/ers-2022-0024.

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Abstract Subject and purpose of work: This paper explores whether herding behavior is formed according to the type of investor, how long the transmission of herding behavior occurs, and identifies how big the reaction of herding behavior is and how the flow of herding behavior connects between investors. Materials and methods: The population in this study are companies whose shares are listed in the LQ45 index list for the period January 2015 to December 2017 on the Indonesia Stock Exchange. To find out further about herding behavior, a VAR test will be conducted in this study. Results: The results of herding behavior analysis, based on the type of investor on the Indonesia Stock Exchange, show that there is herding behavior in each type of similar investor. Moreover, there is a certain period for the spread of herding behavior by type of shareholder. Conclusions: The most influential variables on the four types of successive investors are domestic institutional investors, individual foreigners, domestic individuals, and foreign institutions. The four types of investors respond differently to herding behavior.
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Ryu, Hoyoung, and Sang Hoon Kang. "A study on the characteristics and dynamics of herding behavior in the Korean financial market." Korean Data Analysis Society 25, no. 4 (August 31, 2023): 1403–20. http://dx.doi.org/10.37727/jkdas.2023.25.4.1403.

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This study analyzed the characteristics of herding behavior existing in the Korean financial market and examined the dynamics of herding behavior. First, we analyzed the herding behavior of the Korean financial market using the methodology of Chiang, Zheng (2010). According to the results, herding behavior existed in both the KOSPI market and the KOSDAQ market, and the smaller the company size, the stronger the herding behavior. In addition, the herding behavior appears stronger during the declining market than during the rising market. Next, we analyzed the dynamics between herding behavior and market consensus using the spillover index of Diebold, Yilmaz (2012). As a result of the analysis, the inflow spillover effect of the herding behavior was greater than the outflow spillover effect. This characteristic of herding behavior is stronger during the declining market than during the rising market. These results mean that investors' blind followings become stronger during the declining market. These results are also clearly confirmed in the network topology analyzed by measuring the net pairwise spillover effect.
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Chen, Yi-Chang, Hung-Che Wu, Yuanyuan Zhang, and Shih-Ming Kuo. "A Transmission of Beta Herding during Subprime Crisis in Taiwan’s Market: DCC-MIDAS Approach." International Journal of Financial Studies 9, no. 4 (December 11, 2021): 70. http://dx.doi.org/10.3390/ijfs9040070.

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The aim of this study is to investigate the herding of beta transmission between return and volatility. We have used the dynamic conditional correlation model with the mixed-data sampling (DCC-MIDAS) model for the analysis. The evidence demonstrates that herding is a key transmitter in Taiwan’s stock market. The significant estimation of DCC-MIDAS explains that the herding phenomenon is highly dynamic and time-varying in herding behavior. By means of time-varying beta of herding based on our rolling forecasting method and robustness check of the Markov-switching regression approach using four types of portfolios, the evidence indicates that there are conditional correlations between betas and herding. In addition, it also reveals that herding forms in Taiwan’s markets during the subprime crisis period.
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40

Xu, Rui. "How Herding Behavior Affects Our lives." Journal of Finance Research 1, no. 1 (October 16, 2017): 19. http://dx.doi.org/10.26549/jfr.v1i1.382.

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Herding behavior is an important part of behavioral finance study. In this paper, I focus on the literature reviews of herding behavior along the timeline and explore how it affects our lives. Herding is a double-edged sword with various impacts. I conclude three possible explanations for herding actions based on regret aversion bias, group mind theory and Emergent Norms Theory. The historical evidence on social and economic impact including asset price bubbles, subprime crisis is presented. Although these negative impacts are serious, herding can improve decision-making for people who are less likely to be biased by regret. Herding may also accelerate society's development if we choose the right leader. Finally I would discuss several measures to ease the negative effect of herding behavior.
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41

BenMabrouk, Houda. "Cross-herding behavior between the stock market and the crude oil market during financial distress." Managerial Finance 44, no. 4 (April 9, 2018): 439–58. http://dx.doi.org/10.1108/mf-09-2017-0363.

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Purpose The purpose of this paper is to investigate herding behavior around the crude oil market and the stock market and the possible cross-herding behavior between the two markets. The analysis examines also the herding behavior during financial turmoil and includes the investor sentiment and market volatility. Design/methodology/approach The authors use a modified version of the cross-sectional standard deviation and the cross-sectional absolute deviation to include investor sentiment, financial crisis and market volatility. Findings The authors find that the volatility of the stock market reduces the herding behavior around the oil market and boosts that around the stock market. However, the investors’ sentiment reduces the herding around the stock market and boosts that around the crude oil market. Consequently, the authors can conclude that the herding behavior around the two markets moves inversely and the herding in each market is enhanced by the lack of information in the other market. Research limitations/implications This paper is limited to the herding of stocks around the crude oil market and ignores the possible herding of commodities around the oil market. Originality/value The originality of the paper rests on the study of the possible cross-herding behavior between the oil market and the stock market especially during financial turmoil.
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42

Patwarani, Riza, and Zaafri Husodo. "Examining Herding Behaviour and Its Impact on Stock Market Volatility: Insights from Asian Economies." Jurnal Manajemen Teori dan Terapan| Journal of Theory and Applied Management 16, no. 3 (December 22, 2023): 596–611. http://dx.doi.org/10.20473/jmtt.v16i3.51757.

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Objective: This study empirically investigates herding bias in six key Asian countries—Indonesia, Singapore, Taiwan, China, Hong Kong, and India—across different periods (pre-, during, and post-COVID-19). It analyzes herding behaviour during COVID and non-COVID periods, exploring its impact on volatility and examining asymmetry during bearish and bullish market conditions. Design/Methods/Approach: The investigation employs the Cross-Sectional Absolute Deviation (CSAD) model with a polynomial regression to scrutinize herding behaviour. A GARCH (1,1) volatility model is also established to assess the relationship between herding and volatility. The sample includes daily stock returns from the mentioned countries from January 2, 2019, to September 30, 2023. Findings: The study reveals the presence of herding behaviour in China and Singapore. In Indonesia and China, herding is evident, specifically during and after the COVID period. The research confirms that herding influences volatility and exhibits asymmetry. Herding is more pronounced during bearish market conditions in China, Indonesia, and Taiwan. Originality/Value: This study contributes to the existing literature by providing empirical insights into herding behaviour comparing in Asian markets, while others research usually only focus on one country. This study further distinguishes itself by examining post-pandemic periods, a unique aspect as most studies typically focus only on pre- and during-COVID periods. Including volatility and asymmetry aspects enriches understanding the nuanced relationship between herding and market conditions. Practical/Policy implication: Investors should remain cautious of short-term herding-induced volatility, leveraging stability for consistent profits. Recognizing limited diversification during market losses is crucial. Additionally, governments and regulators should focus on enhancing market transparency and investor education, investing in robust market infrastructure to mitigate the impact of excessive herding.
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LIN, YU-EN, HSIANG-HSUAN CHIH, TAI-HSUN HUANG, and CHIA-HSIEN TANG. "THE DISPOSITION EFFECT, ESCALATION OF COMMITMENT AND HERDING BEHAVIOR OF MUTUAL FUND MANAGERS." Annals of Financial Economics 10, no. 01 (June 2015): 1550003. http://dx.doi.org/10.1142/s2010495215500037.

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This paper investigates the relationship between deposition effect and escalation of commitment and herding behavior. First, this paper ranks the mutual fund into five groups by herding style, and we examine deposition spread (DISP) and escalation of commitment dispread (ESCA) zero investment portfolios in each herding style portfolio. Then, we investigate whether the paper gain ratio or paper loss ratio impacts on herding behavior after controlling other characteristics. Our results can be summarized as follow: First, deposition effect and escalation of commitment has negative impact on mutual fund performance. Second, in buy herding style fund, the deposition effect and escalation of commitment has the most negative impact on performance, however, in sell herding style fund, the negative effect disappears. Finally, we find the deposition effect indeed impacts the herding behavior.
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44

Salamouris, Ioannis S., and Yaz Gulnur Muradoglu. "Estimating analyst's forecast accuracy using behavioural measures (Herding) in the United Kingdom." Managerial Finance 36, no. 3 (February 23, 2010): 234–56. http://dx.doi.org/10.1108/03074351011019564.

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PurposeThe purpose of this paper is to identify herding behaviour on financial markets and measure the herding behaviour impact on the accuracy of analysts' earnings forecasts.Design/methodology/approachTwo alternative measures of herding behaviour, on analysts' earnings forecasts are proposed. The first measure identifies herding as the tendency of analysts to forecast near the consensus. The second measure identifies herding as the tendency of analysts to follow the most accurate forecaster. This paper employs the method of The Generalised Method of Moments in order to relax any possible biases.FindingsIn both measures employed, a positive and significant relation is found between the accuracy of analysts' earnings forecasts and herding behaviour. According to the first measure analysts exhibit herding behaviour by forecasting close to the consensus estimates. According the second herding measure, it is found that analysts tend to herd towards the best forecaster at the time. Finally, it is concluded that the accuracy of analysts' forecasts increases as herding increases.Research limitations/implicationsThe present study triggers concerns for further research in the modelling of analysts' forecasting behaviour.Originality/valueThis paper proposes that a measure based on human biases is the best way to estimate and predict the analysts' earnings forecast future accuracy.
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45

Wong, Yoke-Chen, and Kim-Lian Kok. "HERDING MEASURES IN EQUITY MARKETS: A CASE STUDY OF BURSA MALAYSIA." Labuan Bulletin of International Business and Finance (LBIBF) 7 (December 31, 2009): 13–32. http://dx.doi.org/10.51200/lbibf.v7i.2586.

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This study examines the issue of herding in the Malaysian equity market over the period 1993 – 2004. Using the method proposed by Christie and Huang (1995), we did not detect any evidence of herding for the whole market, the large firms or the small firms during the pre-crisis, crisis and the post-crisis periods. The modified method of Christie and Huang (1995) produced similar findings. However, using the method proposed by Chang et al. (2000), herding was found in the overall market in the whole period. In the pre-crisis period, herding in the market during the market decline could be attributed to both the large and small firms. Rather surprisingly, there was no herding in the crisis period. In the post-crisis period, herding was detected in the market during market rise and this could be attributed to the small firms. Large firms, on the other hand, witnessed herding during market decline. The modified method of Chang et al. (2000) detected more evidence of herding with the use of cross-sectional inter-quartile range but lessevidence of herding when cross-sectional standard deviation is used.
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46

Stavroyiannis, Stavros, and Vassilios Babalos. "Time-varying herding behavior within the Eurozone stock markets during crisis periods." Review of Behavioral Finance 12, no. 2 (July 3, 2019): 83–96. http://dx.doi.org/10.1108/rbf-07-2018-0069.

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Purpose Motivated by the ongoing debate on the existence and magnitude of herding in financial markets, the purpose of this paper is to examine Eurozone stock markets for herding behavior. In the context of the present study, the authors seek for herding behavior of stock markets as a whole as opposed to previous studies that examine herding on stock level. Design/methodology/approach To this end, the authors employ data on benchmark stock market indices for a long sample starting from 2000 through 2016. The testing procedure entails the standard Capital Asset Pricing Model-based procedure along with an advanced econometric method allowing the coefficients of the model to vary over time. Findings Results provide evidence in favor of negative herding behavior (anti-herding) for the Eurozone as a whole with noteworthy transitions. Further analysis reveals that stock markets of the periphery exhibit scarce evidence of herding, whereas continental countries are mainly characterized by negative herding behavior. Originality/value The present study’s main contribution is twofold. First, herding is examined not in sector or stock level as previous studies but at market level. Second, the testing methodology entails a pure time-varying regression model with stochastic volatility proposed by Nakajima (2011) that has not been previously employed in stock market herding. The results entail significant implications for investors seeking for diversification across Eurozone stock markets.
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Effinger, Matthias R., and Mattias K. Polborn. "Herding and anti-herding: A model of reputational differentiation." European Economic Review 45, no. 3 (March 2001): 385–403. http://dx.doi.org/10.1016/s0014-2921(00)00070-2.

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48

Hadady, Hartaty, and Rachman Dano Mustafa. "Investor Herding Behavior in Infrastructure Companies on the IDX: Data Panel Approach." Society 10, no. 2 (December 30, 2022): 375–89. http://dx.doi.org/10.33019/society.v10i2.483.

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This research aims to examine the behavior of herding investors due to the information on interest rates and trading volume. By using daily infrastructure company data on the IDX, it is found that interest rates have a negative effect, while volume has a positive effect on herding behavior. The results show that herding behavior decreases when information on interest rates is entered, while herding behavior increases when there is a trend in trading volume. These results indicate that information announced and scheduled will reduce the behavior of herding investors, such as information about interest rates. On the other hand, investor herding behavior tends to increase when information is random, such as trends in stock trading volumes.
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Ansari, Aleem, and Valeed Ahmad Ansari. "Do investors herd in emerging economies? Evidence from the Indian equity market." Managerial Finance 47, no. 7 (February 15, 2021): 951–74. http://dx.doi.org/10.1108/mf-06-2020-0331.

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PurposeThe purpose of this study is to empirically examine the presence of herding behavior of Indian investors using daily sample data drawn from the Standard and Poor's (S&P) Bombay Stock Exchange-500 Index over the period 2007–2018.Design/methodology/approachThe study employs the model proposed by Chang et al. (2000), taking stock return dispersion as a measure to capture herding. The empirical results demonstrate the absence of herding behavior in all market states, that is, normal, up and down market conditions for the overall period.FindingsContrastingly, the study found negative herding behavior, which underlines that individuals are taking the decision away from the market consensus. The subperiod analysis corroborates the negative herding behavior. The results remain invariant across large, mid and small-capitalization firms except in one year, that is, 2009 for small firms. While using liquidity and sentiment as variables to examine herding, the study finds some evidence of herding behavior for high market liquidity state and sentiment. The findings of negative herding shed new light on herding behavior in the Indian stock market.Originality/valueThis pattern of behavior may indicate irrationality of investor behavior and the presence of noise traders who mistrust market-wide information. Behavioral factors such as overconfidence may explain this pattern of behavior.
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Pan, Wanbin, and Jun Shan. "The structural change of mutual fund herding in China stock market." Corporate Ownership and Control 12, no. 3 (2015): 48–54. http://dx.doi.org/10.22495/cocv12i3p5.

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This paper examines the structural change of mutual fund herding in china stock market，an important investment behavior of institutional investors. A self-normalization based Kolmogorov-Smirnov test is employed to test the change point of herding from 2002 to 2011, the results suggest that there really be structural change points in mutual fund herding. The mutual fund herding changed at December 2004, June 2007 and December 2008. The structural change of the mutual fund herding can be explained by the financial environment of China stock market.
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