Knowledge that Transforms

Cross-stock momentum builds on the asymmetry in lead-lag linkages and the difference between long-run and short-run contemporaneous co-movements. Data-driven cross-stock linkages generate a monthly alpha of 1.62% ( t -stat=10.03). The asymmetry distinguishes cross-stock momentum from factor momentum, and industry momentum is not subsumed by factor momentum. Factor momentum profit is mostly due to the high cross-stock links. The data-driven linkages vary faster over time than those in previous studies because short-run co-movements incorporate persistent linkages.

We study the distributional consequences of student debt forgiveness in present value terms, accounting for differences in repayment behavior across the earnings distribution. Full or partial forgiveness is regressive because high earners took larger loans, but also because, for low earners, balances greatly overstate the benefits of debt cancellation. Consequently, forgiveness would benefit the top decile as much as the bottom three deciles combined. Enrolling households who would benefit from income-driven repayment is less expensive and distributes more funds to lower-income households.

Remote work has increased the demand for housing and changed the demand for the location of that housing. Because housing supply is heterogeneous across space and more elastic in the long-run, the effects on rents and populations may differ over time. We use the lens of a spatial housing model with heterogeneous housing supply elasticities to identify the housing and location demand changes from 2020–2022, and show that the same shocks will have different effects in the long run. Even though rents and prices increased significantly in the short-run, we estimate that in the long-run, increased housing demand will increase rents by only 1.8 percentage points, and that changing location demand will decrease rents by 0.3 percentage points, with a more negative impact on cities in which CPI is measured and cities that were initially expensive.

Screening in consumer credit markets is often associated with large fixed costs. We present both theory and evidence that, when lenders use fixed-cost technologies to screen borrowers, increased competition may increase rather than decrease interest rates in subprime consumer credit markets. In more competitive markets, lenders have lower market shares, and thus lower incentives to invest in screening. Thus, when markets are competitive, all lenders face a riskier pool of borrowers, which can lead interest rates to be higher. We provide evidence for the model’s predictions in the auto loan market using administrative credit panel data.

Empirical asset pricing models with possibly unnecessary risk factors are increasingly common. Unfortunately, they can yield misleading statistical inferences. Unlike previous studies, we estimate the identified set of SDFs and risk prices compatible with a given model’s asset pricing restrictions. We also propose tests that detect problematic situations with economically meaningless SDFs unrelated to the test assets. Empirically, we estimate linear subspaces of SDFs compatible with popular extensions of the traditional and consumption versions of the CAPM, which are typically two-dimensional. Moreover, we often find that all the SDFs in those linear spaces are uncorrelated with the test assets’ returns.

Loan guarantees represent a form of government intervention to support bank lending. However, their use raises concerns as to their effect on bank risk-taking incentives. In a model of financial fragility that incorporates bank capital and a bank incentive problem, we show that loan guarantees reduce depositor runs and improve bank underwriting standards, except for the most poorly capitalized banks. We highlight a novel feedback effect between banks’ underwriting choices and depositors’ run decisions, and show that the effect of loan guarantees on banks’ incentives is different from that of other types of guarantees, such as deposit insurance.

Climate scientists project rising average temperatures and increasing frequency of temperature extremes. We study how extreme temperatures affect corporate profitability across different industries and whether sell-side analysts understand these relationships. We combine granular daily data on temperatures across the continental U.S. with locations of public companies’ establishments and build a panel of quarterly firm-level temperature exposures. Extreme temperatures significantly impact earnings in over 40% of industries , with bi-directional effects that harm some industries while others benefit. Analysts and investors do not immediately react to observable intra-quarter temperature shocks, though earnings forecasts account for temperature effects by quarter-end in many industries.

This paper develops a multi-firm equilibrium model of information acquisition based on differences in firms’ characteristics. The model shows that heightened economic uncertainty amplifies stock price reactions to earnings announcements via increased investor attention, which varies by firm characteristics. Firms with higher systematic risk or more informative announcements attract more attention and exhibit stronger reactions to earnings announcements. Moreover, heightened investor attention caused by high economic uncertainty leads to a steeper CAPM relation and higher betas for announcing firms. Empirical analyses using firm-level attention measures and CAPM tests on high- versus low-attention days support the model’s predictions.

Implicit guarantees provided by financial intermediaries are a key component of China's shadow banking sector. We show theoretically that project screening by intermediaries, accompanied by their implicit guarantees to investors, can be the second-best arrangement and mitigate capital misallocation that favors state-owned enterprises (SOEs). Using a dataset of trusts’ investment products, we find, consistent with our model, that ex ante expected yields reflect borrower risks and implicit guarantee strength, and risk sensitivity is reduced by strong guarantees. Regulations in 2018 restricting implicit guarantees lead to a weaker relationship between yield spread and guarantee strength, and more credit rationing of non-SOEs.

Contrary to the theoretical principle that higher risk is compensated with higher expected return, the literature shows that low-risk stocks outperform high-risk stocks. Using a large-scale household dataset, we provide an explanation for this puzzling result that the anomalous negative risk-return relation is only confined to those stocks predominantly held by rich households, whereas the anomaly disappears for stocks held by non-rich households and institutional investors. We find that social status concern of rich households and the induced lottery preference explain wealthy investors’ demand for high-risk stocks, leading to overpricing and low future returns for such stocks.