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Complicated Firms

Author

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  • Lauren Cohen
  • Dong Lou

Abstract

We exploit a novel setting in which the same piece of information affects two sets of firms: one set of firms requires straightforward processing to update prices, while the other set requires more complicated analyses to incorporate the same piece of information into prices. We document substantial return predictability from the set of easy-to-analyse firms to their more complicated peers. Specifically, a simple portfolio strategy that takes advantage of this straightforward vs. complicated information processing classification yields returns of 118 basis points per month. Consistent with processing complexity driving the return relation, we further show that the more complicated the firm, the more pronounced the return predictability. In addition, we find that sell-side analysts are subject to these same information processing constraints, as their forecast revisions of easy-to-analyse firms predict their future revisions of more complicated firms.

Suggested Citation

  • Lauren Cohen & Dong Lou, 2011. "Complicated Firms," FMG Discussion Papers dp683, Financial Markets Group.
    • Handle: RePEc:fmg:fmgdps:dp683
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    File URL: http://www.lse.ac.uk/fmg/workingPapers/discussionPapers/fmgdps/DP683%20PWC24.pdf
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    Cited by:

    1. Stefan Nagel, 2013. "Empirical Cross-Sectional Asset Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 5(1), pages 167-199, November.
    2. Johannes M. Lehner & David McMillan, 2015. "Making sense in asset markets: Strategies for Implicit Organizations," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1024022-102, December.
    3. Marco Di Maggio & Marco Pagano, 2018. "Financial Disclosure and Market Transparency with Costly Information Processing [Bargaining with incomplete information]," Review of Finance, European Finance Association, vol. 22(1), pages 117-153.

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