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Why you should not use the LSV herding measure

Simon Jurkatis

No 959, Bank of England working papers from Bank of England

Abstract: Here are three reasons. (a) This paper proves that the popular investor-level herding measure is a biased estimator of herding. Monte Carlo simulations demonstrate that the measure underestimates herding by 20% to 100% of the estimation target. (b) The bias varies with the number of traders active in an asset such that regression type analyses using LSV to understand the causes and consequences of herding are likely to yield inconsistent estimates if controls are not carefully chosen. (c) The measure should be understood purely as a test on binomial overdispersion. However, alternative tests have superior size and power properties.

Keywords: Herding; estimation; market microstructure; overdispersion (search for similar items in EconPapers)
JEL-codes: C13 C58 G14 G40 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2022-01-07
New Economics Papers: this item is included in nep-ecm and nep-ore
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