US money market funds (MMFs) play an important role in short-term markets as large investors of Treasury bills (T-bills) and repurchase agreements (repos). We build a theoretical model in which MMFs strategically interact with banks and each other. These interactions generate interdependencies between repo and T-bill markets, affecting the pricing of these near-money assets. Consistent with the model's predictions, we empirically show that when MMFs allocate more cash to the T-bill market, T-bill rates fall, and the liquidity premium on T-bills rises. To establish causality, we devise instrumental variables guided by our theory. Using a granular holding-level dataset to examine the channels, we show that MMFs internalize their price impact in the T-bill market when they set repo rates and tilt their portfolios towards repos with the Federal Reserve when Treasury market liquidity is low. Our results have implications for the transmission of monetary policy, benchmark rates, and government debt issuance.

We explain variation in the strength of the U.S. dollar with capital flows driven by primitive economic factors. Prior to the global financial crisis, global savings and demand shifts depreciated the dollar, whereas they appreciated it after. Interest rates impacted the dollar’s value over short horizons, but declined in significance over longer horizons as rates converged. Our estimates imply that the dollar’s value is stable even when one foreign country unilaterally sells its U.S. assets. However, a weakening global demand for U.S. assets of the same magnitude as the early 2000s could significantly depreciate the dollar.

The United States (US) seems safe relative to the rest of the world (ROW). Her macro quantities, asset prices and wealth share all rise relative to the ROW during global downturns. These novel US safety facts challenge the traditional view that the US exorbitant privilege, the large average excess returns on the US external portfolio, is a risk premium that compensates the US for her role as the global insurance provider. Furthermore jointly accounting for countercyclical dollar and global risk premium dynamics alongside the US exorbitant privilege requires the US to suffer a worse recession than the ROW during global downturns, an implication also at odds with these facts. To resolve this puzzle, I emphasise a novel source of US specialness: her excess fiscal capacity vis-a-vis the ROW. I study the joint dynamics between the US fiscal condition, global innovation and growth, international risk-sharing, the dollar and global risk premia in a quantitative model with risk-sensitive preferences that takes this excess US fiscal capacity as given. The framework quantitatively resolves the US safety puzzle, as well as other stylised facts in international macro-finance. These results therefore tie the excess US fiscal capacity to key puzzling phenomena within the modern global financial system, a novel insight that has received surprisingly little emphasis thus far and has important implications for policy moving forward

We present a new log-linear identity that relates a firm's market value to future markups, output growth, discount rates, and investment in a present-value framework. Expected markups are a dominant contributor to variation in firm values and to the rise in the aggregate market value of U.S. public firms since the 1980s. The rise in aggregate expected markups is driven by reallocation of market share towards higher-markup firms, echoing results for realized markups. Expressing markups in terms of a forward-looking value component rather than realized markups reveals that this reallocation has recently been accelerated by mergers involving highly-valued, high-markup target firms. Expected markups are closely tied to expected fixed costs and investments, including investments in intangibles. We find a a negative time-series relationship between expected markups and discount rates rates, but a positive cross-sectional link to risk premia after accounting for other risk factors, thus reconciling risk-based arguments with theories tying the rise in market power to the fall in interest rates.

I demonstrate that the preference by asset managers to diversify stocks and follow certain investment mandates result in forecastable contrarian trading on their largest positions. Since large-cap stocks are held in similar positions across most asset managers, few equity portfolios are available to absorb this predictable source of demand. The large stock portfolios during the sample period (Q1 1990 to Q2 2021) exhibit a novel return-reversal pattern that is consistent with this demand channel. A variable that forecasts this source of demand for large stocks can explain return reversals in the momentum portfolios formed from the largest US companies.

This paper explores the asset pricing implications of a granular economy, where a few firms are exceedingly large (the size of ’grains’). We present three new findings that support the idea that a more granular economy may be detrimental to investors, due to reduced diversification across stocks and heightened aggregate risk. First, the slope of the Security Market Line (SML) exhibits a negative relationship with the level of granularity. Second, the betting-against-beta (BAB) strategy performs well only during times of increased granularity, aligning with the SML’s decreasing slope. Third, exposure to granularity is negatively priced, indicating that stocks performing well during increased granularity offer protection against diversification risk, thereby providing lower returns. These results underscore the critical role of granularity in understanding vital aspects of equity markets.

We show that net demand in the S&P 500 option market is fundamental to explain empirical puzzles related to the pricing kernel. When public investors (non-market makers) are exposed to variance risk by net-selling out-of-the-money (OTM) options, the pricing kernel is U-shaped, expected option returns are low and the variance risk premium is high. Conversely, when public investors are protected against variance risk by net-buying OTM options, the pricing kernel is decreasing in market returns, expected option returns are high and the variance risk premium is low. Our findings support equilibrium models with heterogeneous agents in which options are nonredundant.

Max Pain price is the strike price at which the total payoff of all options (calls and puts) written on a particular stock, and with the same expiration date, is the lowest. We construct a measure of (potential) Max Pain gain/loss, sort stocks according to this measure, and find that a spread portfolio that buys high Max Pain stocks and sells low Max Pain stocks generates large, positive and statistically significant returns and alphas. Our results provide strong evidence of stock return predictability at the expiration of the options. Finally, we find that these returns reverse after the options expiration week. This is all consistent with stock manipulation on the part of market participants with short positions. Our results are especially strong for relatively small and illiquid stocks.

We document that implied volatility (IV) curves extracted from short-term equity options frequently become concave prior to the earnings announcements day (EAD), typically reflecting a bimodal risk-neutral distribution for the underlying stock price. Firms with concave IV curves exhibit significantly higher absolute stock returns on EAD and higher realized volatility after the announcement, as compared to firms with non-concave IV curves. Hence, concavity in the IV curve constitutes an ex-ante option-based signal for event risk in the underlying stock. Returns on delta-neutral straddles, delta-neutral strangles, and delta- and vega-neutral calendar straddles are all negative and significantly lower in the presence of concave IV curves, showing that investors pay a substantial premium to hedge against the gamma risk arising due to this event.

We recover a stochastic discount factor (SDF) for asset returns from a firm’s investment Euler equation. Given a parametric statistical specification of the SDF and profitability process, we solve for the firms’ optimal investment decision with approximate analytical solutions and provide a dissection of the determinants of real investment. We estimate a specification of the model to discipline the free parameters of the SDF by matching moments of both aggregate real quantities and asset prices. We use the estimated parameters to recover the latent SDF from data on aggregate investment rates, risk-free rates, and profitability growth rates. Innovations in the recovered SDF are driven dominantly by innovations in investment rates and marginally by innovations in risk-free rates and profitability growth rates. The recovered SDF exhibits strong counter-cyclicality with large jumps in recessions and prices standard Fama-French portfolios out of sample reasonably well. Our model allows us to explicitly characterize the risk-free rate, the equity premium, the term structure of interest rates, and the term structure of equity risk premia. The framework we propose here is general and can be extended to accommodate several additional aggregate shocks and frictions that have been proposed in the literature.

The recent linear factor models (e.g., Fama and French (2015) and Hou, Xue, and Zhang (2015)) use total asset growth as the measure of investment, largely due to its stronger return predictive power than its components such as the long-term and current asset growths. We offer an explanation of the latter finding by extending the standard q theory of investment into a two-capital setup in which firms use both long-term and current asset as production inputs. We uncover a novel asset imbalance channel which creates negative comovement between current and long-term asset growths that are unrelated to discount rate. This comovement is muted in the total asset growth, giving rise to its stronger return prediction. Once controlling for this comovement, the return predictive power of current and long-term asset growths substantially improves. Furthermore, we document strong evidences for the model's prediction that the asset growth effects are more prominent among firms with low asset imbalance. Our results support the q theory based explanation for the asset growth effect.

We argue that leasing is an important mitigation channel of credit constraint-induced capital misallocation. However, the existing literature neither includes leased capital in empirically measuring capital allocation efficiency, nor recognizes its mitigation role economically. Empirically, we show that neglecting leased capital and overlooking its mitigation effect leads to significant overestimations of capital misallocation and the cyclicality of capital misallocation. Theoretically, we develop a dynamic general equilibrium model with heterogeneous firms, collateral constraint, and an explicit buy versus lease decision to demonstrate and quantify the role of leasing in mitigating capital misallocation. We provide strong empirical evidence to support our theory.

We study sources and implications of undiversified portfolios in a production-based asset pricing model with financial frictions. Households take concentrated positions in a single firm exposed to idiosyncratic shocks because managerial effort requires equity stakes, and because investors gain private benefits from concentrated holdings. Matching data on returns and portfolios, we find that the marginal investor optimally holds 45% of their portfolio in a single firm, incentivizing managerial effort that accounts for 4% of aggregate output. Investors derive control benefits equivalent to 3% points of excess return, rationalizing low observed returns on undiversified holdings in the data. A counterfactual world of full diversification would feature higher risk free rates, lower risk premiums on fully diversified and concentrated assets, less capital accumulation, yet higher consumption and welfare. Exposure to undiversified firm risk can explain approximately 40% of the level and 20% of the volatility of the equity premium. A targeted subsidy that decreases diversification improves welfare by increasing managerial effort and reducing financial frictions.

Young firms' contribution to aggregate employment has been underwhelming. However, we show that a similar trend is not apparent in their contribution to aggregate sales or stock-market capitalization, suggesting that these firms have exhibited a high ratio of average-to-marginal revenue-product-of-labor. We study the implications of the arrival of such firms in a standard model of dynamic firm heterogeneity, and show that their arrival provides a unified explanation for a large number of facts related to the decline in ``business dynamism''. We provide an analytical framework to gauge the quantitative impact of the decline in business dynamism on aggregate economic activity.

Business cycles are typically associated with lower firm cashflows and higher discount rates. We show that these two components have very different implications for labor income growth. Higher discount rates lead to lower worker earnings for workers at the bottom of the income distribution; these declines are primarily driven by job separations. By contrast, lower cashflow (or productivity) news is followed by declines in earnings for workers in the top of the income distribution, with most of the effect coming from the intensive margin. We build an equilibrium model of labor market search that quantitatively replicates these facts. The model has several implications regarding the role of discount rates in generating unemployment fluctuations; the drivers of the low level of cyclicality of aggregate worker earnings; and the redistributive effects of business cycle fluctuations and monetary policy. These implications are consistent with the data.

I show that an asset pricing model for the equity claims of a value-maximizing firm can be constructed from its optimal financial contracting behavior. Deals between firms and financiers reveal the importance of contractible states for firm's equity value, namely the stochastic discount factor the firm responds to. I empirically evaluate the model in the cross section of expected equity returns. I find that the financial contracting approach goes a long way in rationalizing observed cross-sectional differences in average returns, also in comparison to mainstream asset pricing models.

I analyze welfare in a model of financial markets where information acquisition is endogenous, information has real effects, and all agents are rational. Agents who derive a private benefit from holding the asset (hedgers) and agents who do not (speculators) have different incentives to acquire information. Multiple equilibria may arise but, in a given equilibrium, information acquisition by one type of agent precludes acquisition by the other. Speculators may produce either too little or too much information. Information acquisition by hedgers entails an additional welfare cost because of foregone gains from trade. I discuss regulatory implications.

This paper analyzes insider-trading regulations, focusing on two recent proposals: advance disclosure and ''cooling-off periods.'' The former requires an insider to disclose his trading plan at adoption, while the latter mandates a delay period before execution. Disclosure increases stock price efficiency but has mixed welfare implications. If the insider has large liquidity needs, in contrast to the conventional wisdom from ''sunshine trading,'' disclosure can even reduce the welfare of all investors. A longer cooling-off period increases outside investors' welfare but decreases stock price efficiency. Its implication on the insider's welfare depends on whether the disclosure policy is already in place.

Currencies that are more exposed to US monetary policy yield positive average excess returns. This result holds both for pure monetary policy shocks and for central bank information shocks, identified via sign restrictions on interest rate surprises using high-frequency data. Currency characteristics help explain the heterogeneity of these exposures across currencies and time. We then build exposure indices to gauge this effect around policy announcements. Long-short trading strategies that condition on such exposure indices display significant excess returns after controlling for dollar, carry and momentum factors.

We document that U.S. monetary policy surprises have large, persistent and asymmetric effects on government bond yields worldwide. Moreover, the impact of Fed policy on sovereign debt markets has experienced a structural break around the Global Financial Crisis (GFC). Treasury term premiums increase persistently following Federal Reserve easing shocks until 2007, but show a protracted decline in the post-GFC sample. Advanced and emerging market economy yields essentially mimic the Treasury market's asymmetric response to Fed surprises. While the break of the term premium response to easing shocks around the GFC is consistent with a change in the net duration of primary dealers' Treasury positions, intermediary balance sheet constraints cannot explain the asymmetric effects of monetary policy on yields. The persistent and asymmetric global yield responses are broadly in line with the dynamics of mutual fund

ows following U.S. monetary policy shocks.

This paper studies the feedback between stock market fluctuations and wealth inequality dynamics. We do so by means of a dynamic consumption-based general equilibrium model with endogenous asset returns and a non-degenerate wealth distribution for a continuum of households. Households are heterogeneous in risk aversion and thus choose different expected portfolio returns and portfolio return volatilities, generating time-varying wealth inequality. We show how to solve the model analytically in terms of a cumulant generating function, which encodes information about all the moments of the distribution of risk aversion. With this result, we recover the nobservable distribution of risk aversion using time variation in the slope of the observable equity term structure. We also confront the model with US data on the wealth distribution to recover a second estimate of the distribution of risk aversion. By comparing the two estimates, we show quantitatively that there is significant feedback between stock price dynamics and wealth distribution dynamics

Missing data is a prevalent, yet often ignored, feature of company fundamentals. In this paper, we document the structure of missing financial data and show how to systematically deal with it. In a comprehensive empirical study we establish four key stylized facts. First, the issue of missing financial data is profound:

it affects over 70% of firms that represent about half of the total market cap. Second, the problem becomes particularly severe when requiring multiple characteristics to be present. Third, firm fundamentals are not missing-at-random, invalidating traditional ad-hoc approaches to data imputation and sample selection. Fourth, stock returns themselves depend on missingness. We propose a novel imputation method to obtain a fully observed panel of firm fundamentals. It exploits both time-series and cross-sectional dependency of firm characteristics to impute their missing values, while allowing for general systematic patterns of missing data. Our approach provides a substantial improvement over the standard leading empirical procedures such as using cross-sectional averages or past observations. Our results have crucial implications for many areas of asset pricing.

When expected returns are linear in asset characteristics, the stochastic discount factor (SDF) that prices individual stocks can be represented as a factor model with GLS cross-sectional regression slope factors. Factors constructed heuristically by aggregating individual stocks into characteristics-based factor portfolios using sorting, characteristics-weighting, or OLS cross-sectional regression slopes do not span this SDF unless the covariance matrix of stock returns has a specific structure. These conditions are more likely satisfied when researchers use large numbers of characteristics simultaneously. Methods to hedge unpriced components of heuristic factor returns allow partial relaxation of these conditions. We also show the conditions that must hold for dimension reduction to a number of factors smaller than the number of characteristics to be possible without having to invert a large covariance matrix. Under these conditions, instrumented and projected principal components analysis methods can be implemented as simple PCA on certain portfolio sorts.

We study the size and drivers of non-standard errors (Menkveld et al., 2021) in portfolio sorts across 14 common methodological decision nodes and 40 sorting variables. These non-standard errors range between 0.05 and 0.26 percent and are, on average, larger than standard errors. Supposedly innocuous decisions cause large variation in estimated premiums, standard errors, non-standard errors, and t-statistics. The impact of decision nodes varies widely across sorting variables. Irrespective of choices in portfolio sorts, we find pervasively positive premiums and alphas for almost all sorting variables. This suggests that while the size of these premiums is uncertain, their sign is remarkably stable. Our code is publicly available.