Herding behaviour and volatility clustering in financial markets

Schmitt, Noemi; Westerhoff, Frank

doi:10.1080/14697688.2016.1267391

Cited by 59 publications

(30 citation statements)

References 48 publications

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“…Extreme price changes emerge within their model when the arrival of exogenous sunspots initiates a spontaneous coordination of speculators' trading behavior. Relatedly, Schmitt and Westerhoff (2017b) assume in their asset-pricing model that the correlation between speculators' trading behavior changes slowly with respect to the market's volatility. If volatility increases, speculators become afraid and follow the trading behavior of other speculators more closely.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous speculators and stock market dynamics: a simple agent-based computational model

Schmitt

Schwartz

Westerhoff

2020

The European Journal of Finance

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We propose a simple agent-based computational model in which speculators' trading behavior may cause bubbles and crashes, excess volatility, serially uncorrelated returns, fat-tailed return distributions and volatility clustering, thereby replicating five important stylized facts of stock markets. Since each speculator bets on his own (technical and fundamental) trading signals, stock prices are excessively volatile and oscillate erratically around their fundamental value. However, speculators' heterogeneity occasionally vanishes, e.g. due to panic-induced herding behavior, yielding extreme returns. Lasting regimes with high volatility originate from the fact that speculators extract stronger trading signals out of past stock price movements when stock prices fluctuate strongly. Simulations furthermore suggest that circuit breakers may be an effective tool to combat financial market turbulences.

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Section: Introductionmentioning

confidence: 99%

Heterogeneous speculators and stock market dynamics: a simple agent-based computational model

Schmitt

Schwartz

Westerhoff

2020

The European Journal of Finance

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“…In Schmitt and Westerhoff (2016), for instance, we show that a time-varying correlation of the stochastic trading signals, coupled to the market's volatility, can lead to volatility clustering, even if speculators do not switch between technical and fundamental trading rules.…”

Section: Discussionmentioning

confidence: 99%

Heterogeneity, spontaneous coordination and extreme events within large-scale and small-scale agent-based financial market models

Schmitt

Westerhoff

2017

J Evol Econ

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractWe propose a novel agent-based financial market framework in which speculators usually follow their own individual technical and fundamental trading rules to determine their orders. However, there are also sunspot-initiated periods in which their trading behavior is correlated. We are able to convert our (very) simple large-scale agent-based model into a simple small-scale agent-based model and show that our framework is able to produce bubbles and crashes, excess volatility, fattailed return distributions, serially uncorrelated returns and volatility clustering. While lasting volatility outbursts occur if the mass of speculators switches to technical analysis, extreme price changes emerge if sunspots coordinate temporarily the behavior of speculators.

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“…Herding affects stock price volatility because herding reduces heterogeneity among investors (Xu, Jiang, Chan, & Wu, 2017;(Nianhang et al, 2017;Schmitt & Westerhoff, 2017). As idiosyncratic volatility can be eliminated Estimating the value of idiosyncratic volatility, all of them use a three-factor model (Fama and French, 1992) as the expected return model.…”

Section: Introductionmentioning

confidence: 99%

Idiosyncratic Volatility and Herd Behavior: Indonesia Stock Market Case

Wibowo¹

2019

jbm

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Anomalies revealed by various research of asset pricing models indicate the presence of other risk factors which have not been included in the model. Even the most recent models such as the Fama-French Five Factor still leave several other risk factors included in the error terms produced by the model. An empirical test that tests whether this idiosyncratic risk significantly affects stock returns becomes necessary and urgent in order to obtain a solid theoretical understanding. Empirical tests in emerging market stock markets such as the Indonesia stock exchange are important in sharpening and enriching the understanding of idiosyncratic risk because transactions in emerging market stock markets are more likely to be influenced by the existence of herding behavior where foreign investors or large investors can often direct trading in several stocks. The empirical test of the idiosyncratic risk and herd behavior correlation in the Indonesia stock exchanges shows herd behavior, especially in stocks that have high idiosyncratic risk and occur in the normal period, not in the crisis period. Herd behavior still avoids too much risk taking, as in times of high uncertainty such as during the crisis period.

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Herding behaviour and volatility clustering in financial markets

Cited by 59 publications

References 48 publications

Heterogeneous speculators and stock market dynamics: a simple agent-based computational model

Heterogeneous speculators and stock market dynamics: a simple agent-based computational model

Heterogeneity, spontaneous coordination and extreme events within large-scale and small-scale agent-based financial market models

Idiosyncratic Volatility and Herd Behavior: Indonesia Stock Market Case

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