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Revisiting US Herding – Accounting for the Dynamics

Author

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  • Almgren, Pelle

    (Department of Economics, Lund University)

Abstract

I revisit the US stock market during COVID-19 and investigate the effect of news sentiment and the pandemic on herding behavior in an extended, dynamic, version of the model introduced in Chang et al. (2000). This extension is motivated both econometrically and theoretically and the results indicate that treating herding as a dynamic phenomena may reveal insights into the mechanisms driving this behavior. Evidence of herding is identified in the full ample (12th December 2017 to 18th February 2022) and during the COVID-19 period (20th January 2020 to 18th February 2022), whereas no evidence of herding is found in the pre- COVID-19 sample (12th December 2017 to 19th January 2020). Sentiment is further shown to influence herding in different directions and with different dynamics in the two regimes. While negative sentiment is shown to contemporaneously increase herding during COVID-19, the opposite reaction is found for the pre-pandemic period. Before COVID-19, the initial response to sentiment changes over the week.

Suggested Citation

  • Almgren, Pelle, 2026. "Revisiting US Herding – Accounting for the Dynamics," Working Papers 2026:9, Lund University, Department of Economics.
    • Handle: RePEc:hhs:lunewp:2026_009
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    References listed on IDEAS

    as
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G01 - Financial Economics - - General - - - Financial Crises
    • G40 - Financial Economics - - Behavioral Finance - - - General

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