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Firm Opacity and the Clustering of Stock Prices: the Case of Financial Intermediaries

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Abstract

In this study, we develop and test the hypothesis that because of opacity, the stock prices of financial firms will cluster on round fractions more than the stock prices of non-financial firms. Indeed, we find that the stock prices of opaque financial firms round on nickels and quarters more than the stock prices of less opaque non-financial firms. These results are robust to a battery of robustness tests that include measuring clustering at different frequencies, different econometric specifications, and different matched sample techniques. To draw stronger causal inferences, we use the passing of the Sarbanes-Oxley (SOX) Act as an exogenous shock to the level of transparency in the financial services sector. We find that price clustering decreases more for financial firms than for non-financial firms during the post-SOX regulation period. We also show that, relative to less opaque financial firms, those financial firms that are more opaque experienced the greatest decline in price clustering during the post-SOX period.

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Notes

  1. Other explanations exist for the presence of price clustering. For instance, Niederhoffer and Osborne (1966) and Ikenberry and Weston (2008) argue that prices tend to cluster on round increments because of behavioral reasons. Since individuals typically think in round numbers, they are more likely to trade on round fractions. Therefore, prices may cluster on round numbers because investors are attempting to mitigate cognitive processing costs.

  2. See e.g., Ball et al. (1985), Gwilym et al. (1998a), Sopranzetti and Datar (2002), Gwilym et al. (1998b), Gwilym and Alibo (2003), Ni et al. (2005), Blau et al. (2017) and Davis et al. (2018).

  3. Polonchek and Miller (1996), Babbel and Merrill (2005), Colquitt et al. (2006), Zhang et al. (2009), among others, show that other financial intermediaries, such as insurance companies, exhibit greater information opacity than non-financial intermediaries.

  4. Since many of the rules and regulations associated with the SOX Act affected how companies report earnings and financial statements, we wanted to examine at least a quarter before and after the passing of the Act. We note that the results are stronger as we lengthen the event window surrounding SOX.

  5. The theoretical models of Demsetz (1968), Kyle (1985), Stoll (1989), Glosten and Milgrom (1985), among others, assert that measures such as the bid-ask spread proxy for the level of information asymmetry in financial markets.

  6. We have expanded our set of stock characteristics (i.e. additional k variables, such as spread, illiq, volatility, turnover, and volume) and the results are robust.

  7. The results are robust to the inclusion of day-fixed effects.

  8. We note that Akhibe and Martin (2008) measure opacity using disclosure variables, such as the degree of independence of the audit committee, existence of an independent financial expert on the audit committee, and degree of disclosure through financial footnotes.

  9. Andrade et al. (2014) use Credit Default Swap (CDS) spreads and a structural CDS pricing model to measure firm-level corporate opacity.

  10. The pre-treatment trends in price clustering between financial and non-financial firms are similar, which satisfies the parallel trend assumption for consistent difference-in-difference estimation.

  11. We have replicated the analysis that follows and define opacity using the median and the 90th percentile and find similar results.

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Authors and Affiliations

  1. Department of Finance in the Dawood School of Business, Lahore University of Management Science, DHA Lahore Cantt., Lahore, 54792, Pakistan

    Ahmed Baig

  2. Department of Economics and Finance in the Huntsman School of Business, Utah State University, Logan, UT, 84322, USA

    Benjamin M. Blau & Todd G. Griffith

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  1. Ahmed Baig
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  2. Benjamin M. Blau
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Correspondence to Benjamin M. Blau.

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Baig, A., Blau, B.M. & Griffith, T.G. Firm Opacity and the Clustering of Stock Prices: the Case of Financial Intermediaries. J Financ Serv Res 60, 187–206 (2021). https://doi.org/10.1007/s10693-020-00341-w

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