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A note on the technology herd: evidence from large institutional investors

Josine Uwilingiye (University of Johannesburg, Johannesburg, South Africa)
Esin Cakan (Department of Economics and Business Analytics, College of Business, University of New Haven, West Haven, Connecticut, USA)
Riza Demirer (Department of Economics and Finance, Southern Illinois University Edwardsville, Edwardsville, Illinois, USA)
Rangan Gupta (Department of Economics, University of Pretoria, Johannesburg, South Africa)

Review of Behavioral Finance

ISSN: 1940-5979

Article publication date: 19 June 2019

Issue publication date: 8 August 2019

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Abstract

Purpose

The purpose of this paper is to examine intentional herding among institutional investors with a particular focus on the technology sector that was the driver of the “New Economy” in the USA during the dot-com bubble of the 1990s.

Design/methodology/approach

Using data on technology stockholdings of 115 large institutional investors, the authors test the presence of herding by examining linear dependence and feedback between individual investors’ technology stockholdings and that of the aggregate market. Unlike other models to detect herding, the authors use Geweke (1982) type causality tests that allow authors to disentangle spurious herding from intentional herding via tests of bidirectional and instantaneous causality across portfolio positions in technology stocks.

Findings

After controlling information-based (spurious) herding, the tests show that 38 percent of large institutional investors tend to intentionally herd in technology stocks.

Originality/value

The findings support the existing literature that investment decisions by large institutional investors are not only driven by fundamental information, but also by cognitive bias that is characterized by intentional herding.

Keywords

Citation

Uwilingiye, J., Cakan, E., Demirer, R. and Gupta, R. (2019), "A note on the technology herd: evidence from large institutional investors", Review of Behavioral Finance, Vol. 11 No. 3, pp. 294-308. https://doi.org/10.1108/RBF-08-2017-0086

Publisher

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Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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