Knowledge that Transforms

A number of delta-hedged equity option strategies exhibit very large average returns. We show that much of the profitability of these strategies can be explained by an IPCA factor model. The economic magnitude of the return-adjustment produced by IPCA is impressive: even before transaction costs, the average IPCA alpha of 46 long-short trading strategies constructed on previously discovered signals, is close to zero and contrasts with average realized returns of over 80 basis points per month. Our IPCA model can be used as a benchmark for assessing the performance of other option portfolios.

We document political sentiment effects on U.S. inventors. Democratic inventors are more likely to patent (relative to Republicans) after the 2008 election of Obama but less likely after the 2016 election of Trump. These effects are at least twice as strong among politically active Democrats and are present even within firms and within firm$ × $technology. We also show that partisans tend to cluster in technologies (e.g., Democrats in Biotechnology and Republicans in Weapons), so that sentiment effects aggregate to more patents in the technologies dominated by the winning party.

We study how bank advertising practices contribute to racial disparities in financial markets by steering minorities toward inferior products. We exploit a regulatory change that incentivizes deposit collection at the Freedman’s Savings Bank, the first institution to collect deposits from African Americans post-Emancipation, by facilitating misuse of depositor funds. After deregulation, advertising volume rises, particularly in African American newspapers, leading to increased deposits from Black depositors despite the bank’s insolvency. We identify persuasion as a key mechanism; prescriptive stereotypes and false claims likely amplify advertising’s impact on African Americans, exacerbating historically large depositor losses after the bank’s collapse.

We study the role of brokers in selection markets. We find broker-clients in the Canadian mortgage market are observationally different from branch-clients. They finance larger loans with more leverage and longer amortization. We build and estimate a model of mortgage demand to disentangle three possible explanations for these riskier product choices: (1) selection on observables, (2) unobserved borrower preferences for riskier loans, and (3) a causal effect of brokers. Although we find that brokers influence product choices, the main reason borrowers choose high-leverage products is unobserved preferences. Borrowers prefer larger loans and brokers facilitate qualification for them.

I study the real effects of centralized derivative markets using the staggered introduction of futures contracts for different steel products in the United States. Employing a difference-in-differences strategy, I find that the arrival of centralized futures markets improves price transparency and risk management in the underlying product market: price dispersion decreases and steel producers increase their hedging activity. Moreover, market share is reallocated toward low-cost producers, while product prices, producers’ profits, and valuations decrease. Overall, the results indicate that centralized futures markets foster competition in the product market.

This paper examines whether capital structure is irrelevant for enterprise value and investment when investors care about environmental, social, and governance issues, which we refer to as “ESG-Modigliani-Miller” (ESG-MM). Theoretically, we show that ESG-MM holds with linear pricing and additive ESG. ESG-MM means that issuing low-yielding green bonds does not lower the overall cost of capital because it makes the issuer’s other securities browner. Hence, a firm’s incentive to make a green investment does not depend on its financing choice. We provide suggestive evidence of failure of ESG-MM, implying that firms and governments can exploit inconsistent ESG attribution or segmented markets.

We offer new evidence on the relationship between competition and innovation that overcomes two measurement difficulties compromising the extant literature: aggregation at either firm level (or higher) of innovative activity, and the mediating influence of distance-to-technological-frontier. FDA awards of Breakthrough Therapy Designations (BTDs) on specific drugs, instrument stochastic unleveling of therapeutic (ie, product) markets. Rivals’ innovative responses generally show an inverted-U pattern in ex ante competitiveness of the shocked market. However, the shape of the relation changes with distance to technological frontier in that market, proxied by whether the rival project uses one of the technologies embedded in the BTD-awarded drug.

We present a model rationalizing the economic value of digital tokens for launching peer-to-peer platforms. By using the blockchain to transparently distribute tokens before the platform launches, a token sale overcomes later coordination failures between the platform’s users. This result follows from forward induction reasoning, under which the costly and observable action of token acquisition credibly communicates the intent to participate on the platform. Our framework demonstrates the applications of digital tokens to entrepreneurship, and offers guidance for both practitioners and regulators.

Single women invest less in risky assets than do single men. This paper analyzes the determinants of the “gender investment gap” based on a structural life-cycle framework. The model can rationalize the gender investment gap without gender heterogeneity in preferences. Rather, lower deterministic income and larger household sizes shift the composition of single women toward poorer households that invest less risky (composition effect). Additionally, future outcomes of both variables (which cannot easily be controlled for in regressions) make single women more vulnerable to financial shocks and decrease their optimal equity share even conditional on state variables (policy effect).

The U.S. stock market’s return during the first month of a quarter correlates strongly with returns in future months, but the correlation is negative if the future month is the first month of a quarter, and positive if it isn’t. These correlations offset, consistent with the well-known near-zero unconditional autocorrelation, yet they are pervasive, present across industries and countries. The pattern accords with a model in which investors extrapolate announced earnings to predict future earnings, not recognizing that earnings in the first month of a quarter are discretely less predictable than in prior months. Survey data support the model.