Using mutual fund flows, we evaluate prospect theory with choice outcomes in the market. We provide strong support for prospect theory: under a standard set of parameters, funds whose past returns generate higher prospect theory value attract significantly larger future flows; we also find corroborative evidence using account-level data. Taking a revealed preference approach, we estimate the prospect theory parameters through a discrete choice model and find that our field-based estimates align well with previous experiment-based estimates. Moreover, we show that prospect theory offers a new framework for understanding flows, as it has explanatory power beyond existing drivers.

We find that common ownership among acquirers enhances rather than hinders competition in the firm sale process. One common owner raises the likelihood that target firms are sold through auction (vs. negotiation with one buyer) by 21.5%. The effect is causal according to identifications based on mergers between financial institutions. Exploring economic channels, we observe selling firms respond to common ownership among acquirers by avoiding cross-owned acquirers, bargaining hard, and inviting more buyers when cross-owned acquirers initiate the deal but not by terminating the deal. Consistent with enhanced competition, common ownership among acquirers is positively associated with deal quality.

Previous work shows large differences in fees for S&P 500 index funds and other funds and suggests that investors suffer wealth losses investing in high-fee funds when similar low-fee funds are available. In contrast, the neoclassical model of mutual funds (Berk and van Binsbergen, 2015, J. Financ. Econ., 118, 1–20) argues that percentage fees are irrelevant, as fund size will adjust in equilibrium such that net alphas are equal to zero. We show that fees matter from an investor perspective. We document (i) a strong negative association between net-of-fee fund performance and fees in a sample of all US and international equity funds, (ii) economically large, robust, persistent, and pervasive fee dispersion in the mutual fund industry, and (iii) important economic effects for investors. During the sample period, the mutual fund industry has generated a total value lost (i.e., a negative net value added) of 125 billion USD, coming predominantly from high-fee funds.

We introduce and test a firm-level innovation-efficiency measure new to the finance literature. The measure, termed the research quotient (RQ), defined as the firm-specific output elasticity of research and development (R&D), was first developed in the management literature. RQ has a low correlation with existing innovation input, output, and efficiency measures. We test RQ in a number of innovation tests common to the finance literature and find that RQ is robust in all tests of firm value, even after controlling for previous innovation measures. The results suggest that RQ may serve as a relevant complementary measure of a company’s innovation.

We present results from an experiment where participants have access to automated trading algorithms, which they may deploy at will while still trading manually. Treatments differ in whether robots must not be halted, deployment is compulsory, or robots can be halted and replaced at will. We hypothesize that robot trading would reduce mispricing, and that the effect would be more pronounced as commitment degree increases. Yet, compared to manual trading only, we observe equally large and frequent mispricing and, in early trading, significantly higher bid–ask spreads and more frequent flash crashes/price surges. Participants earn more, provided they combine robot and manual trading. Compared to evidence from archival data, we find significantly higher use of liquidity-taking robots. We attribute this to the inability, in the field, to identify the presence of liquidity takers when they happen not to trade.