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Why you should not use the LSV herding measure

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  • Jurkatis, Simon

    (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.

Suggested Citation

  • Jurkatis, Simon, 2022. "Why you should not use the LSV herding measure," Bank of England working papers 959, Bank of England.
    • Handle: RePEc:boe:boeewp:0959
    as

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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Herding; estimation; market microstructure; overdispersion;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G40 - Financial Economics - - Behavioral Finance - - - General

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