Skip to main content
Article
Institutional Ownership and Return Predictability Across Economically Unrelated Stocks
Journal of Financial Intermediation (2016)
  • George P. Gao, T. Rowe Price
  • Pamela Moulton, Cornell University
  • David T. Ng, Cornell University
Abstract
We document strong weekly lead-lag return predictability across stocks from different industries with no customer-supplier linkages (economically unrelated stocks). Between 1980 and 2010, the industry-neutral long-short hedge portfolio earns an average of over 19 basis points per week. This predictability is related to common institutional ownership and is distinct from previously documented lead-lag effects. Common institutional ownership is a complementary rather than a substitute explanation for return predictability. Information linkages are enough to induce return predictability among stocks in the same industry, but economically unrelated stocks exhibit return predictability only when they have common institutional owners. Our findings suggest that institutional portfolio reallocations can induce return predictability among otherwise unrelated stocks.
 
Keywords
  • return predictability; anomalies; institutional ownership; institutional trading,
  • JEL G12,
  • JEL G14
Publication Date
August 1, 2016
DOI
10.1016/j.jfi.2016.07.004
Publisher Statement
Required Publisher Statement
© Elsevier. Final version forthcoming: Gao, G. P., Moulton, P. C., & Ng, D. T. (2017). Institutional ownership and return predictability across economically unrelated stocks. Journal of Financial Intermediation, doi:10.1016/j.jfi.2016.07.004
Reprinted with permission. All rights reserved.
Citation Information
Gao, G. P., Moulton, P. C., & Ng, D. T. (2017). Institutional ownership and return predictability across economically unrelated stocks [Electronic version]. Retrieved [insert date], from Cornell University, School of Hotel Administration site: https://works.bepress.com/pamela_moulton/
Creative Commons license
Creative Commons License
This work is licensed under a Creative Commons CC_BY-NC-ND International License.