Corporate innovation, q-theory of investment, behavioral finance
Using Patent Capital to Estimate Tobin's q
I construct a new proxy for Tobin's q that incorporates the replacement cost of patent capital. This proxy, which I call patent q, explains up to 62% more variation in investment than other proxies for q. Furthermore, investment is more sensitive to patent q than to other proxies for q. Although investment is predicted more accurately by, and is more sensitive to, patent q, controlling for patent q leads to relatively higher, not lower, cash flow coefficients. All results are stronger in subsamples with more patent capital. Overall, patent q strengthens the historically weak investment-q relation.
Small Innovators: No Risk, No Return (with Noah Stoffman and M. Deniz Yavuz)
We show that the disclosure of patent grants by small, innovative firms is associated with higher long-term returns. We provide robust evidence that this relation is driven by risk, not underpricing. Our results are consistent with small innovators being risky due to their reliance on external parties for commercializing their patents. Specifically, we find that the returns of small innovators increase with financial constraints and reliance on strategic alliances. The higher cost of equity among small innovators has implications for their investment, growth, and capital structure decisions.
Price-Path Convexity, Extrapolation, and Short-Horizon Return Predictability (with Zhi Da and Huseyin Gulen)
The curvature of intramonth stock price paths, which is distinct from cumulative return over the same period, contains significant additional return predictive power. In the cross section, stocks with the least convex price paths subsequently outperform stocks with the most convex price paths. This effect ranges from 1.34% to 1.53% per month and is not driven by small stocks, the bid-ask bounce, or other short-term return predictors. We find similar results in different time periods, in non-US G7 countries, and even at the aggregate market level. We argue that price-path convexity uniquely captures investor over-extrapolation of recent price changes. Therefore, our results provide broad evidence that extrapolative expectations are an important contributor to short-horizon return predictability.