University of South Carolina
Darla Moore School of Business
1014 Greene St
Columbia, SC 29208
Institutional Affiliation: University of California, San Diego
Information about this author at RePEc
NBER Working Papers and Publications
|May 2017||Innovative Originality, Profitability, and Stock Returns|
with , : w23432
We propose that innovative originality (InnOrig) is a valuable organizational resource, and that owing to limited investor attention and skepticism of complexity, firms with greater InnOrig are undervalued. We find that firms’ InnOrig strongly predicts higher, more persistent, and less volatile profitability; and higher abnormal stock returns—findings that are robust to extensive controls. The return predictive power of InnOrig is stronger for firms with higher valuation uncertainty, lower investor attention, and greater sensitivity of future profitability to InnOrig. This evidence suggests that innovative originality acts as a ‘competitive moat,’ and that the market undervalues InnOrig.
Published: David Hirshleifer & Po-Hsuan Hsu & Dongmei Li, 2018. "Innovative Originality, Profitability, and Stock Returns," The Review of Financial Studies, vol 31(7), pages 2553-2605. citation courtesy of
|September 2008||Costly External Finance: Implications for Capital Markets Anomalies|
with : w14342
In a frictionless world, investment is perfectly elastic to changes in the discount rate. With financial frictions, investment is less elastic, meaning that a given magnitude of change in investment is associated with a higher magnitude of change in the discount rate. Equivalently, investment is a more powerful predictor of future stock returns. Consistent with this prediction, we document that the asset growth, external finance, and accrual anomalies in the cross-section of stock returns are much stronger in financially more constrained firms than in financially less constrained firms. Further tests show that this effect of financial constraints is distinct from the effect of financial distress and the effect of limits of arbitrage on the magnitude of the anomalies.