POWER OF CSAD-BASED TEST ON HERDING BEHAVIOR
Abstract
This study aims to answer the question of whether the cross-sectional absolute deviation (CSAD)-based test is powerful enough to detect herding behavior in financial markets. Using US stocks as the main sample, I investigate the power of the CSAD-based test as a herding detection method, with a focus on two dimensions: the self-consistency of the method and the power of t-tests used in the method. I find that conducting the tests with a large number of stocks over extended time periods is likely to provide consistent conclusions on whether herding behavior exists in the stock market. These findings support the CSAD-based test as a herding detection method. However, with an overall mean of 59.37%, the estimated power of t-tests can be as low as 37.62%, indicating low testing power. Therefore, researchers should be careful when using the CSAD-based test as a herding detection method, especially when R^2s are low.
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