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Emerging capital markets constitute environments whose institutional structures innately
facilitate the manifestation of herd behavior (Gelos and Wei, 2002). Normally operating
in jurisdictions under incomplete regulatory frameworks (Antoniou et al., 1997a) and
inadequate or ill-enforced provisions, these markets are susceptible to adverse practices
including rumor-mongering (Van Bommel, 2003) and manipulation (Allen and Gale,
1992). Consequently, this leads to the transparency of the informational environment
being compromized, thus fostering the development of collective trading tendencies
among investors.
The above-mentioned scenarios have prompted a large amount of empirical research
on the premises of both microdata (Choe et al., 1999; Kim and Wei, 2002a, 2002b; Bowe
and Domuta, 2004; and Voronkova and Bohl, 2005) as well as aggregate data (Demirer and
Kutan, 2006; Farber et al., 2006; and Ha, 2007) with results largely confirming the presence
of significant herding in the developing market settings. A characteristic feature of the
latter is that they tend to accommodate substantial levels of thin trading, whose presence
has been found (Antoniou et al., 1997a) to be associated with the introduction of biases
in empirical estimations in finance literature. Despite a large number of herding studies
that have included emerging markets in their design, the possibility of thin trading
conferring such a bias over herding estimates appears to have received relatively little
attention.
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