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Found 6417 results for '"Herding "', showing 1-10
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  1. Raphaëlle Bellando (2012): The bias in a standard measure of herding
    We address the Lakonishok, Shleifer and Vishny (LSV) herding measure. ... Using a theoretical model we provide a formal explanation of this bias, and show that a corrected herding measure depends on some unobservable parameters. This suggests that assessing herding intensity with this kind a more difficult task than considered up to now in the empirical literature.
    RePEc:ebl:ecbull:eb-12-00111  Save to MyIDEAS
  2. Philippas, Dionisis & Philippas, Nikolaos & Tziogkidis, Panagiotis & Rjiba, Hatem (2020): Signal-herding in cryptocurrencies
    The paper examines the influence of informative signals derived from exogenous factors on herding intensity in the cryptocurrency market. ... The signals may induce investors to converge towards (depart from) the market consensus, contributing to herding amplification (dampening). The findings reveal substantial asymmetries with respect to the intensity of herding stemming from exogenous influences.
    RePEc:eee:intfin:v:65:y:2020:i:c:s1042443120300755  Save to MyIDEAS
  3. D. Sgroi (2001): Controlling the Herd: Applications of Herding Theory
    The literature on informational cascades and herding theory has for a decade focused on the externality and suboptimal outcomes generated from decision-making when spaces are coarser than private information spaces. ... This paper redresses this imbalance by detailing several direct applications for marketing and business arising from herding theory. We see that business practices such as encouraging early sales, or selling to groups rather than individual customers, can be justified theoretically by direct application of herding theory.
    RePEc:cam:camdae:0106  Save to MyIDEAS
  4. Ray Saadaoui Mallek & Mohamed Albaity & Philip Molyneux (2021): Uncertainty, Trust and Herding Behaviour
    This study examined the impact of uncertainty and trust (in institutions) on the herding behaviour of investors in 32 OECD stock markets between 2003 and 2018. Overall, we found that uncertainty and trust weakened both investor’s herding and antiherding behaviour.
    RePEc:afj:journ3:v:11:y:2021:i:2:p:94-106  Save to MyIDEAS
  5. Rocco Ciciretti & Ambrogio Dalò & Giovanni Ferri (2021): Herding and Anti-Herding Across ESG Funds
    We investigate to what extent ESG funds present an herding/anti-herding behavior, and the consequences of their investment strategies in terms of both systematic risk exposure and risk-adjusted returns. Our findings document that ESG funds pursue an anti-herding strategy that leads to higher risk-adjusted returns.
    RePEc:rtv:ceisrp:524  Save to MyIDEAS
  6. Andrea Morone (2008): Simple Model Of Herd Behaviour, A Comment
    In his ‘Simple model of herd behaviour’, Banerjee (1992) shows that – in a sequential game – if the first two players have chosen the same action, all subsequent players will ignore their own information and start a herd, an irreversible one. ... Its weakness is that it is based on three tie-breaking assumptions, which according to Banerjee minimise herding probabilities. ... Even if the overall probability of herding does not change dramatically, the results obtained, which differ from Banerjee's are the following: players' strategies are parameter dependent; an incorrect herd could be reversed; a correct herd is irreversible. There are, in addition, some several cases where available information allows players to find out which action is correct, and so an irreversible correct herd starts.
    RePEc:eei:rpaper:eeri_rp_2008_12  Save to MyIDEAS
  7. Morone, Andrea (2008): Simple model of herd behaviour, a comment
    In his ‘Simple model of herd behaviour’, Banerjee (1992) shows that – in a sequential game – if the first two players have chosen the same action, all subsequent players will ignore their own information and start a herd, an irreversible one. ... Its weakness is that it is based on three tie-breaking assumptions, which according to Banerjee minimise herding probabilities. ... Even if the overall probability of herding does not change dramatically, the results obtained, which differ from Banerjee's are the following: players' strategies are parameter dependent; an incorrect herd could be reversed; a correct herd is irreversible. There are, in addition, some several cases where available information allows players to find out which action is correct, and so an irreversible correct herd starts.
    RePEc:pra:mprapa:9586  Save to MyIDEAS
  8. Zhao, Yuan & Liu, Nan & Li, Wanpeng (2022): Industry herding in crypto assets
    Using price information extracted from coinmarketcap.com between 29 April 2013 and 9 May 2022, we find evidence of herding and reverse herding in the crypto assets market. Concentrated periods of herding and reverse herding are particularly evident in the January 2020–April 2022 Covid period. At industry level, herding is more profound in large sectors with higher volatility. ... We also detect varying asymmetric herding at industry level. This paper further examines the factors that drive such industry herding and reverse herding in the crypto assets market, and our results show that industry concentration and investor sentiments contribute to the probability of herding/reverse herding.
    RePEc:eee:finana:v:84:y:2022:i:c:s1057521922002848  Save to MyIDEAS
  9. Marco Cipriani & Antonio Guarino (2015): Herd Behavior in Financial Markets
    Over the last twenty-five years, there has been a lot of interest in herd behavior in financial markets—that is, a trader’s decision to disregard her private information to follow the behavior of the crowd. A large theoretical literature has identified abstract mechanisms through which herding can arise, even in a world where people are fully rational. Until now, however, the empirical work on herding has been completely disconnected from this theoretical analysis; it simply looked for statistical evidence of trade clustering and, when that evidence was present, interpreted the clustering as herd behavior. However, since decision clustering may be the result of something other than herding—such as the common reaction to public announcements—the existing empirical literature cannot distinguish “spurious” herding from “true” herd behavior.
    RePEc:fip:fednls:87015  Save to MyIDEAS
  10. TAUFEEQ AJAZ & ANOOP S. KUMAR (2018): Herding In Crypto-Currency Markets
    We test for herding in crypto-currency markets using the CSAD method of Chang et al. (2000). ... Possibility of herding under up and down market and high and low volatility is tested. Herding is found under up and down market activity, indicating over-enthusiasm and over-reaction. Market volatility is found not to have any significant impact on herding behavior. Herding is found to be dependent upon the market activity rather than market volatility.
    RePEc:wsi:afexxx:v:13:y:2018:i:02:n:s2010495218500069  Save to MyIDEAS
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