Journal of Financial Economics最新文献

We propose a formal statistical test to compare asset-pricing models in the presence of price impact. In contrast to the case without trading costs, we show that in the presence of price-impact costs different models may be best at spanning the investment opportunities of different investors depending on their absolute risk aversion. Empirically, we find that the five-factor model of Hou et al. (2021), the six-factor model of Fama and French (2018) with cash-based operating profitability, and a high-dimensional model are best at spanning the investment opportunities of investors with high, medium, and low absolute risk aversion, respectively.

Investment-based asset pricing models typically predict a close link between a firm’s stock return and its characteristics at any point in time. Yet, previous studies have primarily focused on the weaker prediction that this link holds on average, finding substantial empirical support. We show how to incorporate the time-series predictions in the estimation and testing of investment-based models using the generalized method of moments. We find that standard specifications of investment-based models with one physical capital input fail to match the time series properties of stock returns in the data, and discuss the implications of the findings for future research.

We study the extent to which time-variation in market betas influence estimates of CAPM alphas. Given the observed variation in conditional market betas, market risk premia, and market variance, the required compensation for conditional market risk can, in theory, be as large as the unconditional equity premium. We implement the conditional CAPM using state-of-the-art methods in a broad global sample. We find that accounting for conditional risk helps explain the return on all the major anomalies we consider and that conditional risk explains two percentage points of alpha for value, investment, and momentum strategies in recent years.

This paper studies the rise of direct lending using a comprehensive dataset of investments by business development companies (BDC). We exploit three exogenous shocks to credit supply, including new banking regulations and a major finance company collapse, to establish that BDC capital acts as a substitute for traditional financing. Using firm-level data, we further document that firms’ access to BDC funding stimulates their employment growth and patenting activity. Beyond credit provision, BDCs contribute to firm growth through managerial assistance.

We examine the pricing of sustainability-linked bonds (SLBs), where the cash flows depend on the bond issuer achieving one or more Environmental, Social and Governance (ESG) goals. Investors are willing to accept a 1–2bps lower yield due to the bond’s ESG label, providing evidence of investors caring about environmental impact. Furthermore, we find the average probability of missing the target is 14%–39% so firms set ESG targets that are easy to reach. We find that the SLB market is efficient: the prices of SLBs depend strongly on the size of the potential penalty and there is no evidence of mispricing. Finally, our results suggest that SLBs serve as financial hedges against ESG risk.

RMBS sponsors contributed to the rise of new product features in securitized mortgages prior to the 2008 financial crisis. Using a regulatory shock to sponsor competition , we show securitization influences the design of mortgage contracts, empirically demonstrating a unique, feedback loop of product differentiation from the derived security (MBS) to the underlying asset (loans). Product differentiation in Prime MBS collateral rises faster than that of non-prime in the early boom period (2000–2004), a strategic choice by MBS sponsors in the face of increasing competition. At very high levels of competition, product differentiation targets non-prime (marginal) borrowers. We develop a theoretical framework for sponsor-induced product differentiation that explains these empirical findings.