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A dynamic analysis of the neglected firm effect

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  • Andrikopoulos, Athanasios
  • Zheng, Min

Abstract

This study uses rolling regressions with panel data and conducts a dynamic analysis of the neglected firm effect, the negative relationship between the number of analysts and stock returns. For this reason, we use two samples of firms: one from the London Stock Exchange (LSE) and another from Bursa Malaysia (BM). The results reveal a significantly negative neglected firm effect only for the BM sample. In contrast the association between the number of analysts and stock returns is positive in some periods in the LSE. Size is not significant as a moderator, which suggests that the neglected firm effect does not vary with firm size, contrary to the findings in the previous literature. Finally, the neglected firm effect is nonstationary for both LSE and BM firms. Our results hold under a range of robustness tests and yield guidelines for investors regarding the types of markets and time periods for which analyst coverage is likely to matter most.

Suggested Citation

  • Andrikopoulos, Athanasios & Zheng, Min, 2023. "A dynamic analysis of the neglected firm effect," International Review of Financial Analysis, Elsevier, vol. 85(C).
    • Handle: RePEc:eee:finana:v:85:y:2023:i:c:s1057521922003799
    DOI: 10.1016/j.irfa.2022.102429
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    More about this item

    Keywords

    Neglected firm effect; Stock returns; Rolling regressions; Moderation effects; Nonstationarity;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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