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Volume
20, No. 1, June 2021
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Analysis of Sectoral
Herding through Quantile Regression: A Study of
S&P BSE 500 Stocks
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Vijay Kumar Shrotryia
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Department of Commerce,
Faculty of Commerce and Business, Delhi School of
Economics, University of Delhi, India
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Himanshi Kalra*
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Department of Commerce,
Faculty of Commerce and Business, Delhi School of
Economics, University of Delhi, India
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Abstract
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The current study
empirically investigates sector-wide flock activity
for the S&P BSE 500 stocks over 8 years spanning
from October 2010 till September 2018. Drawing on
absolute deviation model by Chang et al. (2000), the
present analysis tends to unravel the curvilinear
relationship between consensus return and dispersion
via Ordinary Least Squares and Quantile Regression
approaches. Using conventional regression, a
nonexistent herd hunch is inferred under both normal
and asymmetric scenarios. However, the examination of
distribution tails discovers herding in auto and
engineering sector during bull markets and healthcare
sector during bearish conditions. However, the two
crises namely the oil crisis of 2014 and the Chinese
crash of 2015 subject the Indian bourse to mimicking
behavior. This may be a matter of concern for the
policy makers as the evidences reflect on the unstable
nature of the S&P BSE 500 index and the Indian
stock market as a whole. Therefore, the regulatory
bodies have to make consistent efforts to bridge the
informational distance between various classes of
investors and corporate houses to ensure more
transparent and honest practices so that investors can
make informed and better decisions. Finally, the
investors may resort to active trading rules during
turbulence to earn more than what market warrants.
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Key words
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Herding; Ordinary Least
Squares; Quantile Regression; Indian Stock Market
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JEL
classification
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C3; C31; G1; G4; G41
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