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2021 | OriginalPaper | Buchkapitel

The Curious Case of Herding: Theories and Risk

verfasst von : Tselika Maria

Erschienen in: Financial Risk Management and Modeling

Verlag: Springer International Publishing

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Abstract

Since the rise of social sciences, researchers struggle to determine the procedure through which individuals decide. As states Lionel Robbins (1932). An Essay on the Nature and Significance of Economic Science, London: Macmillan, “Economics is the science which studies human behaviour as a relationship between ends and scarce means which have alternative uses.”

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Vorheriges Kapitel Climate Change and Financial Risk

As agents keep stocks that have had a negative performance and prefer to sell stocks that perform well.

For example the conjunction fallacy, the gambler’s fallacy and the hot hand fallacy that can be observed in the short persistence for specific stocks that have a negative performance or a positive trend while ignoring the fundamentals (Gilovich et al. 1985; Carhart 1997).

This is known as framing effect.

Noise traders, under informed or under skilled investors, fund managers for reputational or compensational reasons.

For example the setting of Avery and Zemsky (1998).

A well-informed agent would rationally follow his own information.

Mostly fundamental information regarding assets.

Limited attention usually manifests in financial markets as the inclination of investors to prefer cognitively-wise familiar information.

As in most empirical methodologies they use Bayesian techniques to analyse their data.

Also shown in Jiang and Verardo (2018).

If we assume that herding is not spurious as some critics tend to argue.

This is indicated by the small numbers of pension funds.

Mostly to draw comparisons regarding experience.

As market return researchers refer to the unweighted or weighted average of the returns of N stocks. If by market we refer to the stocks included in an index then r _m,t may also refer to the return of the index.

Capital Asset Pricing Model.

The measure of herding they use is supposed to follow an autoregressive stationary process of order one and the estimation of the dispersion of time varying βs is not properly justified.

Variables that are also affiliated to specific regions that have more in common than culture.

About the intensity of herding we can find some measures in the literature (Patterson and Sharma 2006) but they have not been sufficiently tested and they examine very specific data and situations.

The opposite is true for the case of herding out of a stock.

An example of this sort is market concentration.

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Titel: The Curious Case of Herding: Theories and Risk
verfasst von: Tselika Maria
Verlag: Springer International Publishing
Buch: Financial Risk Management and Modeling
Print ISBN: 978-3-030-66690-3

Electronic ISBN: 978-3-030-66691-0

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-66691-0_13