Corporate innovation, mergers and acquisitions, 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.
We show that small innovators (i.e., small firms with recent patent grants) earn higher future returns than small non-innovators. However, we find no such innovation premium among large firms. The higher returns are driven by risk, not underreaction to announcements of recent patent grants. We find that being small and innovative interacts with financial constraints to explain the higher returns. These interactions are more important in the presence of greater information asymmetry. 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 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 leads to annualized Sharpe ratios of over 1.00. Our results are not driven by stocks of small firms, 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.
Works in Progress
Patent Thickets and Mergers and Acquisitions (with Logan Emery)
We examine the relation between patent thickets, which are dense webs of overlapping intellectual property rights that increase the costs of patent commercialization, and the likelihood of merger pair formation. We find that firms in denser external patent thickets, which expose firms to these costs, are less likely to be targets. Conversely, firms in denser internal patent thickets, which insulate firms from these costs, are more likely to be targets. The likelihood of merger pair formation increases with the extent to which the acquirer is in the same external patent thicket as the target, and the strength of this relation increases in the density of the external thicket. Overall, our results provide the first evidence that patent thickets are an important consideration for mergers and acquisitions.