The Psychology of Herding
Kok Loang Ooi (),
Norazlin Binti Ab Aziz () and
Wee Yeap Lau ()
Additional contact information
Kok Loang Ooi: Universiti Malaysia
Norazlin Binti Ab Aziz: Universiti Malaysia
Wee Yeap Lau: Universiti Malaysia
Chapter Chapter 1 in Following the Crowd: Psychological Drivers of Herding and Market Overreaction, 2025, pp 1-22 from Springer
Abstract:
Abstract Herding behaviour in financial markets refers to investors’ collective tendency to imitate the actions of others, often leading to market inefficiencies, speculative bubbles, and economic disasters. This chapter examines the psychological underpinnings of herding and highlights the influence of social proof and conformity on financial decision-making. This chapter elucidates how cognitive and social variables influence herd behaviour, drawing on Solomon Asch’s conformity studies, Robert Shiller’s concept of irrational exuberance, and Amos Tversky’s theory of heuristics and biases. The analysis of historical and current instances underscores the significance of herding in today’s financial markets, where digital platforms and algorithmic trading have intensified collective decision-making tendencies. Comprehending the psychological foundations of herding is essential for investors, regulators, and financial institutions to mitigate the risks associated with pervasive market behavioural biases.
Date: 2025
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-95-0792-4_1
Ordering information: This item can be ordered from
http://www.springer.com/9789819507924
DOI: 10.1007/978-981-95-0792-4_1
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().