How does common ownership affect innovation? We study this question using project-level data on pharmaceutical startups and their venture capital (VC) investors. We find that common ownership leads VCs to hold back projects, withhold funding, and redirect innovation at lagging startups. Effects are stronger where R&D costs are larger, consistent with common owners aiming to cut duplicate costs. Effects are also stronger where technological similarity is greater and preexisting competition is lower, consistent with common owners seeking market power for their surviving projects. Overall, common VC ownership appears to generate social benefits , via improved innovation efficiency, but also social costs

I examine the asset pricing implications of technological innovations that allow capital to displace labor: automation. I develop a theory in which firms with displaceable labor are negatively exposed to such technology shocks. In the model, firms optimally adopt technology to gain competitive advantage but in equilibrium competition erodes profits and decreases firm value. Empirically, I find that firms with high share of displaceable labor have negative exposure to technology shocks. A long-short portfolio sorted on this variable mimics macroeconomic measures of technology shocks. Negatively exposed firms earn a 4% annual return premium consistent with displacement risk from technological progress

Some events impact volatilities of most assets, asset classes, sectors and countries, causing serious damage to investment portfolios. The magnitude of such shocks is defined as global COVOL which is an abbreviation for global common volatility, a broad measure of all types of global financial risk. This paper introduces a statistical formulation of such events as common volatility innovations in both a multivariate volatility and an asset pricing context. Simulations verify the statistical performance of a simple but novel estimator and of a test to detect global COVOL. Two empirical examples show the events that have had the biggest impact on financial markets. The results are useful for portfolio optimization and risk forecasting