Knowledge that Transforms

We provide the first systematic asset pricing analysis of one of the main safe asset categories, the repurchase agreement (repo). Based on the temporal and cross-sectional variation in short-term rates, we form a carry that, together with a market factor, prices these near-money assets in a linear pricing model. The carry depicts heterogeneity in nonpecuniary convenience yields of collateral assets and increases in the safety premium and the liquidity premium reflecting opportunity cost. Our carry helps explain the cross-section of short-term rates, as well as of long-term bond returns after accounting for standard bond pricing factors.

We develop a model of information and portfolio choice in which ex ante identical investors choose to specialize because of fixed attention costs required in learning about securities. Without this friction, investors would invest in all securities and would be indifferent across a wide range of information choices. When securities’ dividends depend on an aggregate (macro) risk factor and idiosyncratic (micro) shocks, fixed attention costs lead investors to specialize in either macro or micro information. Our results favor Samuelson’s dictum that markets are more micro than macro efficient. We derive testable predictions from our model and find empirical support for our predictions in specialization by U.S. equity mutual funds.

We develop a new approach to determine investors’ risk compensations for all distributional moments of a security. Using the concept of entropy, which is a summary of all moments of a risky security, we derive the relationship between expected returns and their compensation for entropy risk. Entropy risk premium (ERP), which is entropy under the physical minus the risk-neutral measure, indicates the hedging cost against changes in risks associated with all moments of the return’s distribution. Applying our model to the commodity markets, we find that ERP carries economically significant information for the cross-section of returns that is different from individual or combined moments.

This paper investigates the firm-level, asset pricing implications of government expenditures. Higher government sales dependency (GD), unconditional on political partisanship cycles, significantly predicts positive future returns, and a GD-weighted portfolio substantially improves the tangency portfolio’s ex post Sharpe ratio. Conditionally, the results are stronger during Republican presidencies. Higher returns do not stem from political connections or political and regulatory risks. The underlying economic channel is higher expected cash flow from increased profitability. Atypical provisions of government contracts and information asymmetry likely drive higher profit margins. A risk versus a mispricing analysis elicits more convincing evidence for mispricing as an explanation for abnormal returns.

We perform portfolio-level analyses to understand insurance firms’ preferred habitat behavior in the government bond market. Based on portfolio durations and portfolio weights across maturities, we find that interest rate risk exposures of insurers’ portfolios are related to their operating liabilities and financing constraints. We show that this habitat behavior significantly affects bond pricing. During the “quantitative easing” era, bond purchases by the Federal Reserve have a larger impact on the yields of Treasury bonds with a higher habitat demand.

The value effect and the idiosyncratic volatility (IVol) discount arise because growth firms and high IVol firms beat the CAPM during periods of increasing aggregate volatility (market volatility and average IVol), that makes their risk low. All else equal, growth options’ value increases with volatility, an effect that is stronger for high IVol firms, for which growth options take a larger fraction of the firm value and firm volatility responds more to aggregate volatility changes. The factor model with the market factor, the market volatility risk factor, and the average IVol factor explains the value effect and the IVol discount.

Predicted stock issuers (PSIs) are firms with expected high-investment and low-profit profiles that earn extremely low returns. We evaluate alternative explanations for this empirical phenomenon. Our results show top-PSI firms are cash-strapped, have lottery-like payoffs, high volatility, high beta, low liquidity, and high shorting costs. Over the next 2 years, top-PSI firms earn return on assets of −30% per year, report disappointing earnings, and experience strongly negative forecast revisions. They perform poorly in down markets and are six times more likely to delist for performance-related reasons. Overall, we find substantial support for mispricing, some support for nonstandard preferences, and virtually no support for the risk explanation.

This paper explores the impact of product market competition on the positive relation between labor mobility (LM) and future returns. We develop a production-based model and formalize the intuition that low exposure to systematic risk in a concentrated industry limits LM’s amplifying effect on operating leverage. Therefore, the model predicts a stronger positive relation between LM and expected returns for firms in competitive industries. Consistent with the model’s prediction, we empirically find that LM predicts returns only among firms in competitive industries. This evidence suggests that the intensity of competition in firms’ product market potentially drives the positive LM-return relation.

We study whether subadvising abroad provides an information advantage that improves the performance of international equity mutual funds. We find that it does not. In fact, internationally outsourced funds underperform on a risk-adjusted basis by up to 162 bps annually. The underperformance is concentrated in funds managed by single subadvisors, who are less likely to be terminated after poor performance compared to funds with multiple subadvisors. We dissect fund performance by the location of its subadvisors and find that international subadvisors underperform primarily in their local holdings. Finally, we show that the industry is nonetheless on a path toward equilibrium.

Through textual analyses of 7.7 million patents, we develop a novel intercompany innovation similarity measure which enables us to find that technologically connected firms cross-predict one another’s returns. Investors impound information about firms’ technological connectedness, although not immediately and fully. Buying (shorting) shares of technological peers earning high (low) returns during the previous month yields a 1.29% monthly return. Firms’ return predictability increases with patent complexity or limited technological disclosures but decreases with better information transparency. Results suggest that investor inattention explains technology momentum. Unlike momentum stemming from simpler, class-based technological links, our Big Data text-based return predictability remains active.