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We construct a novel data set to show that, between 2003-2020, up to one-fifth of America's largest firms had a non-financial blockholder or insider as their largest shareholder. Blockholders and insiders tend to be less diversified than institutional investors. Measures of "universal" and "common" ownership of firms are therefore lower than previously believed based on analyses of institutional investors' holdings alone, and the heterogeneity in ownership structures across firms is greater. Consolidation in the asset management industry increases universal ownership and common ownership of industry rivals. Extant results claiming indexing alone explains the rise of universal ownership cannot be confirmed with the new, more comprehensive data.

We show that the main claim in Dennis, Gerardi, and Schenone (JF forthcoming) (DGS), namely "that the documented positive correlation between common ownership and ticket prices stems from the market share component of the common ownership measure, and not the ownership and control components," is factually incorrect. In particular, we show empirically that the placebo that according to DGS "keeps market shares fixed" is in fact highly negatively correlated with market shares. This correlation is mechanical and arises because the data set is an unbalanced panel, as we show analytically. We make a methodological contribution to the literature by showing how one can actually separate variation from market shares from variation in ownership. Contrary to DGS' claims, ownership changes do predict price changes once one constructs a valid placebo that actually separates the variation from market shares from the variation in ownership. AST's panel regressions in fact underestimated the price effect of common ownership, due to the endogeneity of market shares.

Economic theory suggests that monopoly prices hurt consumers but benefit shareholders. But in a world where individuals or households can be both consumers and shareholders, the impact of market power on inequality depends in part on the relative distribution of consumption and corporate equity ownership across individuals or households. The paper calculates this distribution for the United States, using data from the Survey of Consumer Finances and the Consumer Expenditure Survey, spanning nearly three decades from 1989 to 2016. In 2016, the top 20 percent consumed approximately as much as the bottom 60 percent, but had 13 times as much corporate equity. Because ownership is more skewed than consumption, increased mark-ups increase inequality. Moreover, over time, corporate equity has become even more skewed relative to consumption.

We study optimal security design when the issuer and market participants agree to disagree about the characteristics of the asset to be securitized. We show that pooling assets can be optimal because it mitigates the effects of disagreement between issuer and investors, whereas tranching a cash-flow stream allows the issuer to exploit disagreement between investors. Interestingly, pooling and tranching can be complements. The optimality of debt with or without call provisions can be derived as a special case. In a model with multiple financing rounds, convertible securities naturally emerge to finance highly skewed ventures.

When Bayesian risk-averse investors are uncertain about their assets’ cash flows’ exposure to systematic risk, stock prices react more to news in downturns than in upturns, implying higher volatility in downturns and negatively skewed returns. The reason is that, in good times, less desirable assets with low average cash flows and high loading on market risk perform similar to more desirable assets with high average cash flows and low market risk, rendering them difficult to distinguish. However, their relative fundamental performance diverges in downturns, enabling better inference. Consistent with these predictions, stocks’ reaction to earnings news is up to 70% stronger in downturns than in upturns..

We provide a model that rationalizes variation in confidence in the time series and the cross section. Combining horizon-dependent risk aversion (“anxiety”) and selective memory, we show that overly precise beliefs (“overconfidence”) can arise in the equilibrium of a Bayesian agent’s intrapersonal game. In the time series, overconfidence is more prevalent when actual risk levels are high, while underconfidence occurs when risks are low. As more confident agents take more risk, fluctuations in confidence amplify boom-bust cycles. More anxious agents’ beliefs fluctuate more, leading them to buy in booms and sell in crashes.

We propose a model that addresses two fundamental challenges concerning the timing and pricing of uncertainty: established equilibrium asset pricing models require a controversial degree of preference for early resolution of uncertainty and do not generate the downward-sloping term structure of risk premia suggested by the data. Inspired by experimental evidence, we construct dynamically inconsistent preferences in which risk aversion decreases with the temporal horizon. The resulting pricing model can generate a term structure of risk premia consistent with empirical evidence, without forcing a particular preference for resolution of uncertainty or compromising the ability to match standard moments.

We study general equilibrium asset prices in a multi-period endowment economy when agents' risk aversion is allowed to depend on the maturity of the risk. We find horizon-dependent riskaversion preferences generate a decreasing term structure of risk premia if and only if volatility is stochastic. Our model can thus justify the recent empirical results on the term structure of risk premia if the pricing of volatility risk is downward sloping (in absolute value) in the data and if downward-sloping term structures of returns on a given market are driven solely by exposures to volatility risk. We test these predictions by estimating the price of volatility risk using index options data and by showing that the value premium is related to the exposure to volatility risk.

Motivated by individuals' emotional response to risk at different time horizons, we model an 'anxious' agent - one who is more risk averse with respect to imminent risks than distant risks. Such preferences describe well-documented features of 1) individual behavior, 2) equilibrium prices, and 3) institutions. In particular, we derive implications for financial markets, such as overtrading and price anomalies around announcement dates, as well as a downward-sloping term structure of risk premia, which are found empirically. Since such preferences can lead to dynamic inconsistencies with respect to risk trade-offs, we show that costly delegation of investment decisions is a strategy used to cope with 'anxiety.'