Analyzing 563 trillion possible models, we find that the majority of tradable factors designed to price bond markets are unlikely sources of priced risk, and only one novel tradable bond factor, capturing the bond post-earnings announcement drift, should be included in the stochastic discount factor (SDF) with very high probability. Nevertheless, the SDF is dense in the space of observable factors, with both nontradable and equity-based ones being salient for pricing corporate bonds. A Bayesian model averaging–SDF explains corporate risk premia better than all existing models, both in- and out-of-sample, and captures business cycle and market crash risks.

Are there risk factors that are pervasive across all major classes of corporate securities, including stocks, bonds, and options? We employ a novel procedure that builds

on the ability of asset characteristics to capture the dynamics of asset returns to estimate a conditional latent factor model. A common risk factor structure prominently

emerges across asset classes. The first factor that corresponds to the dominant principal component of the joint cross section significantly explains a substantial component

of time-series variation of individual asset returns across all three asset classes, has a

Sharpe ratio over twice that of the stock market. Other common factors that are less

pervasive, i.e. describe a smaller portion of common variation in returns over time.

Some of the common factors highly correlated with some of asset-class-specific factors

as well as several macroeconomic and financial variables. However, we also document

that the factor structure does not fully capture the cross-section of average returns.

Portfolios that have zero loadings on the top latent risk factors can earn substantial

Sharpe ratios, with different asset classes hedging each other’s exposures to the common

factors.

I show that non-linear pricing of market risk can explain many prominent cross-sectional stock return anomalies, such as momentum, betting-against-beta, idiosyncratic volatility, and liquidity. The non-linear pricing model is inferred from options data without assumptions on the pricing relationship. I further document that many anomalies have a strong tail risk exposure, which is successfully priced by the model. A key feature of the model is a sizable upside risk premium of approximately 4% per annum. Finally, the pricing results can be explained with a compensation for exposure to systematic variance risk.

Contrary to existing literature, we establish that two factors, dollar and carry, suffice to explain a large cross-section of currency returns with R2s exceeding 80%. Our paper highlights the importance of accounting for time-variation in conditional moments. Unconditional estimations that ignore this time-variation mistakenly reject the two-factor model. We propose a parsimonious framework to estimate conditional currency factor models and provide testable restrictions. Our findings imply that currency markets are well described by a model in which (i) each country-specific SDF loads on one country-specific—dollar—and one global—carry shock, and (ii) risk loadings are time-varying. Other risk factors proposed in the literature are useful to describe the time variation in dollar and carry factor risk premia.

We show that country risk premia include compensation for global political risk. Political risk premia drive international returns within and across asset classes, including equities, bonds, and currencies. A strong factor structure in politically sorted portfolios uncovers systematic variations in global political risk (P-factor). The P-factor commands a significant risk premium of 4.44% per annum with a Sharpe ratio of 0.70, and together with the global market portfolio, it explains up to three-quarters of cross-sectional variation in a large panel of asset returns. The P-factor is unspanned by the existing asset pricing factors, manifests in all asset classes, and is related to systematic variations in expected global growth and aggregate volatility.

We provide a unified explanation for two important trends during the last few decades: the decline of the value premium and the rise of the markup. We show that the decline of the value premium and the rise of the markup are primarily driven by firms with high markups, whereas the value premium and the markup remain stable in firms with low markups. We develop a dynamic model with stochastic technology frontier and heterogeneity in firms' technology adoption decisions to explain this finding. In the

model, by adopting the latest technology firms on the technology frontier reduce the operating costs in production, which in turn increases the markup and decreases the dispersion in their exposures to the aggregate technology frontier shocks. This leads to the rise of the markup and the decline of the value premium among the high markup firms. For firms that cannot catch up with the technology frontier due to adoption costs, they keep operating the old technology, thus the markup stays low and the value premium remains sizable.

We study the welfare implications of the rise of common ownership in the United States from 1994 to 2018. We build a general equilibrium model with a hedonic demand system in which firms compete in a network game of oligopoly. Firms are connected through two large networks: the first reflects ownership overlap, the second product market rivalry. In our model, common ownership of competing firms induces unilateral incentives to soften competition. The magnitude of the common ownership effect depends on how much the two networks overlap. We estimate our model for the universe of U.S. public corporations using a combination of firm financials, investor holdings, and text-based product similarity data. We perform counterfactual calculations to evaluate how the efficiency and the distributional impact of common ownership have evolved over time. According to our baseline estimates the welfare cost of common ownership, measured as the ratio of deadweight loss to total surplus, has increased nearly tenfold (from 0.3% to over 4%) between 1994 and 2018. Under alternative assumptions about governance, the deadweight loss ranges between 1.9% and 4.4% of total surplus in 2018. The rise of common ownership has also resulted in a significant reallocation of surplus from consumers to producers.

We study the inflation implications for firms across the market power distribution

from an asset pricing perspective. Inflationary surprises are associated with

persistent declines in stock returns. We propose a new decomposition of the present

value identity of stock prices and show that investors expect nominal cashflows to

remain stagnant during periods of higher-than-expected inflation, a stagflationary

view of the world, on average, while a rising equity risk premium reduces stock

prices. Real yields do not increase in response to inflationary news, inconsistent

with a Taylor-rule type monetary policy-driven stock price response. Firms with a

large degree of market power are shielded from the negative returns following inflation

surprises, as market power firms are expected to generate a relative increase

in their nominal cashflows in response to inflation shocks. Changes in analysts’

firm-level earnings expectations around inflationary surprises confirm these results.

We explore the asset pricing implications of shocks that allow firms to extract more rents from consumers. These markup shocks directly impact the representative household's marginal utility and the firms' cash flow. Using firm-level data, we construct a measure of aggregate markup shocks and show that the price of markup risk is negative, that is, a positive markup shock is associated with high marginal utility states. Markup shocks generate differences in risk premia due to their heterogeneous impact on firms. Firms with larger exposures to markup shocks are less risky and have lower expected returns. We rationalize these findings in a general equilibrium model with markup shocks.

We document that 20% of Compustat firms have above-median investment rates despite having below-median marginal product of capital (MPK), seemingly "misallocating" productive resources. These firms are typically younger and significantly more likely to experience a substantial upward jump in their sales and MPK in the following years. They account for a significant share of innovative activity and their investments predict future aggregate productivity in the economy, creating value in ways not captured by their MPK. We propose and estimate a simple endogenous firm growth model that captures the key features of the cross-section of firms and allows for counterfactual analysis. Hypothetical firm investment policies that ignore the potential for future jumps reduce MPK and investment dispersion but also lower aggregate productivity.

U.S. stocks' response to inflation surprises is, on average, robustly negative and shows pronounced time-series variability. Consistent with a view that stock prices respond to inflation surprises that affect the monetary policy stance, we document the largest stock market sensitivity during periods when inflation expectations and the output gap are running high. During these periods, firms with low net leverage, large market capitalization, high market beta, low book-to-market, and low markups are especially susceptible to inflation surprises.

We introduce a novel log-linear identity linking a company's market value to expected future markups, output growth, discount rates, and investments within a present-value framework. By distinguishing between realized and expected markups, we unveil five new empirical facts. (i) Expected markups account for one-third of the rise in aggregate firm values of U.S. public firms since 1980. (ii) The rise in aggregate expected markups is driven by a reallocation of market share towards high-expected-markup firms. Mergers have accelerated this trend with expected (but not realized) markups rising post merger. (iii) Expected markups are closely tied to fixed costs and investments, particularly in intangibles. (iv) There is a negative time-series relationship between expected markups and discount rates, but (v) there is a positive cross-sectional link to risk premia after accounting for other risk factors. These five facts can guide the development of macro-finance models.

U.S. firms have reduced their investment in scientific research (“R”) compared to product development (“D”), raising questions about the returns to each type of investment, and about the reasons for this shift. We use Census data that disaggregates “R” from “D” to study how US firms adjust their innovation investments in response to an external increase in funding cost. Companies with greater demand for refinancing during the 2008 financial crisis, made larger cuts to R&D investment. This reduction in R&D is achieved almost entirely by reducing investment in research. Development remains essentially unchanged. If other firms patenting similar technologies must refinance, however, then Development investment declines. We interpret the latter result as evidence of technological competition: firms are reluctant to cut Development expenditures when that could place them at a disadvantage compared to potential rivals.

We provide the first large-sample evidence of substantial anticipatory effects: firms are affected by proposed rules long before those are finalized. We construct a new data set that tracks the timeline of each rule proposal developed by federal agencies since 1995, total of 43,000 proposals. The average proposal spends more than two years in the rulemaking pipeline and only two-thirds convert into a final rule. Training a machine-learning algorithm, we derive a firm-level measure of exposure to the regulatory pipeline: the amount of rule proposals which are relevant to the firm. We find that firms with greater exposure increase overhead costs, reduce capital investments, and report lower profits, independent of their current regulatory burden and political risk. The effects increase with the expected burden of the proposals and when agencies develop rules outside of their core expertise. Calibrating a latent factor model of stock returns with our new firm-specific measure, we identify systematically important regulatory topics such as Securities, Natural Resources, and Environment. Our results are the first to document anticipatory effects based on the entire body of potential federal regulations.

Innovation booms are often fueled by easy financing that allows new technology firms to pay high wages that attracts skilled labor. Using the late 1990s Information and Communication Technology (ICT) boom as a laboratory, we show that skilled labor joining this new sector experienced sizeable long-term earnings losses. We show these earnings patterns are explained by faster skill obsolescence rather than either worker selection or the overall bust in the ICT sector. During the boom, financing flowed more to firms whose workers would experience the largest productivity declines, amplifying the negative effect of labor reallocation on aggregate human capital accumulation.

We open the black box of corporate innovation production by examining its most important input: the employees tasked with creating new inventions. Using a novel within-firm research design involving the universe of U.S. corporate inventors across four decades, we find that inventors’ shared cultural values are a critical driver of inventor team formation. Moreover, using premature co-inventor deaths as exogenous shocks to team composition, we document both positive and negative impacts of inventor team cultural diversity on team patent production. Less culturally diverse teams produce a higher overall quantity of patents that tend to exploit existing technologies, while more culturally diverse teams produce more risky, exploratory patents with a greater potential for high-impact innovations. Exploring the underlying mechanisms, we present evidence that culturally diverse teams tend to seek new knowledge from more heterogeneous and non-traditional input information sources, but they also face greater knowledge integration challenges. Overall, our results present a more nuanced perspective on diversity, revealing that it does not lead to uniformly better or worse outcomes, but instead impacts the type of R&D output.

Analyzing millions of patents granted by the USPTO between 1970 and 2020, we find a pattern where specific patents only rise to prominence after considerable time has passed. Amongst these late-blooming influential patents, we show that there are key players (patent hunters) who consistently identify and develop them. Although initially overlooked, these late-bloomer patents have significantly more influence on average than early-recognized patents and open significantly broader new markets and innovative spaces. For instance, they are associated with a 15.6% (t = 29.1) increase in patenting in the late-bloomer’s technology space. Patent hunters, as early detectors and adopters of these late-blooming patents, are also associated with significant posi- tive rents. Their adoption of these overlooked patents is associated with a 22% rise in sales growth (t = 6.55), a 3% increase in Tobin’s Q (t = 3.77), and a 4.8% increase in new product offerings (t = 2.25). We instrument for patent hunting and find similarly large positive impacts on firm value. Interestingly, these rents associated with patent hunting on average exceed those of the original patent creators themselves. Patents hunted tend to be closer to the core technology of the hunters, more peripheral to the writers, and to be in less competitive spaces. Lastly, patent hunting appears to be a persistent firm characteristic and to have an inventor-level component as well.

We document a form of "excess" commitment to R&D projects and examine the consequences for innovation outcomes and consumer welfare, using detailed data on pharmaceutical firms' clinical trial projects. Plausibly-exogenous delays in the completion of the preceding trial-phase, empirically uncorrelated with various project-quality measures, substantially reduce firms' subsequent project termination propensity. This excess project commitment intensifies when the CEO has higher stock-price-compensation sensitivity and is personally responsible for the project’s initiation. Welfare implications are nuanced: delay-driven commitment induces investment crowd-out, while not predicting increased adverse effects in marginally-launched drugs and predicting continuation of drugs for diseases lacking alternative treatments.