Knowledge that Transforms

ABSTRACT Should regulators reveal the models they use to stress‐test banks? In our setting, revealing leads to gaming, but secrecy can induce banks to underinvest in socially desirable assets for fear of failing the test. We show that although the regulator can solve this underinvestment problem by making the test easier, some disclosure may still be optimal (e.g., if banks have high appetite for risk or if capital shortfalls are not very costly). Cutoff rules are optimal within monotone disclosure rules, but more generally optimal disclosure is single‐peaked. We discuss policy implications and offer applications beyond stress tests.

ABSTRACT We use retail structured equity product (SEP) issuances to construct a new sentiment measure for large capitalization stocks. The SEP sentiment measure predicts negative abnormal returns on the SEP reference stocks based on a variety of factor models, and also predicts returns in Fama‐MacBeth regressions that include a wide range of covariates. Consistent with our interpretation that SEP issuances reflect investor sentiment, aggregate SEP issuances are highly correlated with the Baker‐Wurgler sentiment index. Tobit regressions reveal that proxies for attention and sentiment predict SEP issuance volumes, providing additional evidence consistent with the hypothesis that SEP issuances reflect sentiment.

ABSTRACT This paper studies the role of moral hazard and liquidity in driving household bankruptcy. First, I estimate that increases in potential debt forgiveness have a positive, but small, effect on filing using a regression kink design. Second, exploiting quasi‐experimental variation in mortgage payment reductions, I estimate that filing is five times more responsive to cash‐on‐hand than relief generosity. Using a sufficient statistic, I show the estimates imply large consumption‐smoothing benefits of bankruptcy for the marginal filer. Finally, I conclude that 83% of the filing response to dischargeable debt comes from liquidity effects rather than a moral hazard response to financial incentives.

ABSTRACT We propose a novel framework for analyzing linear asset pricing models: simple, robust, and applicable to high‐dimensional problems. For a (potentially misspecified) stand‐alone model, it provides reliable price of risk estimates for both tradable and nontradable factors, and detects those weakly identified. For competing factors and (possibly nonnested) models, the method automatically selects the best specification— if a dominant one exists—or provides a Bayesian model averaging–stochastic discount factor (BMA‐SDF), if there is no clear winner. We analyze 2.25 quadrillion models generated by a large set of factors and find that the BMA‐SDF outperforms existing models in‐ and out‐of‐sample.

ABSTRACT In this address, I discuss differences across investor and manager motivations for considering sustainable finance— value versus values motivations—and how these differences contribute to misunderstandings about environmental, social, and governance investment approaches. The finance research community has the ability and responsibility to help clear up these misunderstandings through additional research, which I suggest.

ABSTRACT We offer a general equilibrium analysis of cryptocurrency pricing. The fundamental value of the cryptocurrency is its stream of net transactional benefits, which depend on its future prices. This implies that, in addition to fundamentals, equilibrium prices reflect sunspots. This in turn implies multiple equilibria and extrinsic volatility, that is, cryptocurrency prices fluctuate even when fundamentals are constant. To match our model to the data, we construct indices measuring the net transactional benefits of Bitcoin. In our calibration, part of the variations in Bitcoin returns reflects changes in net transactional benefits, but a larger share reflects extrinsic volatility.

ABSTRACT We propose a duration‐based explanation for the premia on major equity factors, including value, profitability, investment, low‐risk, and payout factors. These factors invest in firms that earn most of their cash flows in the near future and could therefore be driven by a premium on near‐future cash flows. We test this hypothesis using a novel data set of single‐stock dividend futures, which are claims on dividends of individual firms. Consistent with our hypothesis, the expected Capital Asset Pricing Model alpha on individual cash flows decreases in maturity within a firm, and the alpha is not related to the above characteristics when controlling for maturity.

ABSTRACT We construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and nonvisual object characteristics. We find that higher automated valuations relative to auction house presale estimates are associated with substantially higher price‐to‐estimate ratios and lower buy‐in rates, pointing to estimates' informational inefficiency. The relative contribution of machine learning is higher for artists with less dispersed and lower average prices. Furthermore, we show that auctioneers' prediction errors are persistent both at the artist and at the auction house level, and hence directly predictable themselves using information on past errors.

ABSTRACT We show that information aggregation in primary financial markets fails precisely when investors hold socially useful information for screening projects. Being wary of the Winner's Curse, less optimistic investors refrain from making financing offers, since their offers would be accepted only when a project is unviable. Their information is therefore lost. The Winner's Curse and associated information loss grow with the number of informed market participants, so that larger markets can lead to worse financing decisions and higher cost of capital for firms seeking financing. Precommitment to ration fundraising allocations, collusive club bidding, and shorting markets can mitigate the inefficiency.

ABSTRACT I present a dynamic general equilibrium model in which commonality in bank assets endogenously changes over the business cycle and shapes systemic risk. To reduce individual risks, banks diversify, increasing portfolio overlap and hence the similarity of their exposures to fundamental shocks. Systemic financial crises burst at the end of credit booms when productive investment opportunities are exhausted, banks' diversification incentives are strong, and their portfolios are highly correlated. A calibrated model is able to match key moments related to frequency, severity, and the economy's behavior around systemic crises.