We use data from the Panel Study of Income Dynamics to investigate how households' portfolio allocations change in response to wealth fluctuations. Persistent habits, consumption commitments, and subsistence levels can generate time-varying risk aversion with the consequence that when the level of liquid wealth changes, the proportion a household invests in risky assets should also change in the same direction. In contrast, our analysis shows that the share of liquid assets that households invest in risky assets is not affected by wealth changes. Instead, one of the major drivers of household portfolio allocation seems to be inertia: households rebalance only very slowly following inflows and outflows or capital gains and losses.

We find that several recently proposed consumption‐based models of stock returns, when evaluated using an optimal set of managed portfolios and the associated model‐implied conditional moment restrictions, fail to capture key features of risk premiums in equity markets. To arrive at these conclusions, we construct an optimal Generalized Method of Moments (GMM) estimator for models in which the stochastic discount factor (SDF) is a conditionally affine function of a set of priced risk factors, and we show that there is an optimal choice of managed portfolios to use in testing a null model against a proposed alternative generalized SDF.

This paper introduces a new metric, α, to benchmark the performance of individual private equity funds. Our metric is substantially less sensitive to noise in fund cash flows compared to the popular public market equivalent (PME) and its generalization (GPME), while having the same aggregate pricing implications as GPME. For a large data set of fund cash flows, α estimates have much lower standard deviation across funds than does (G)PME. For buyout funds, PME and α are close, but deviate in certain subsamples. Using α increases power in regressions involving fund performance and improves performance predictability of future funds.

Building on evidence that lifetime experiences shape individuals’ macroeconomic expectations, we study asset prices in an economy in which a representative agent learns with fading memory about unconditional mean endowment growth. With IID fundamentals, constant risk aversion, and memory decay calibrated to microdata, the model generates a high and strongly countercyclical objective equity premium, while the subjective equity premium is virtually constant. Consistent with this theory, experienced payout growth (a weighted average of past growth rates) is negatively related to future stock market excess returns and subjective expectations errors in surveys, and positively to analysts’ forecasts of long-run earnings growth.

We adapt structural models of default risk to take into account the special nature of bank assets. The usual assumption of lognormally distributed asset values is not appropriate for banks. Typical bank assets are risky debt claims with concave payoffs. Because of the payoff nonlinearity, bank asset volatility rises following negative shocks to borrower asset values. As a result, standard structural models with constant asset volatility can severely understate banks’ default risk in good times when asset values are high. Additionally, bank equity return volatility is much more sensitive to negative shocks to asset values than in standard structural models.

We argue that tests of reduced‐form factor models and horse races between “characteristics” and “covariances” cannot discriminate between alternative models of investor beliefs. Since asset returns have substantial commonality, absence of near‐arbitrage opportunities implies that the stochastic discount factor can be represented as a function of a few dominant sources of return variation. As long as some arbitrageurs are present, this conclusion applies even in an economy in which all cross‐sectional variation in expected returns is caused by sentiment. Sentiment‐investor demand results in substantial mispricing only if arbitrageurs are exposed to factor risk when taking the other side of these trades.

How do individuals form expectations about future inflation? We propose that individuals overweight inflation experienced during their lifetimes. This approach modifies existing adaptive learning models to allow for age-dependent updating of expectations in response to inflation surprises. Young individuals update their expectations more strongly than older individuals since recent experiences account for a greater share of their accumulated lifetime history. We find support for these predictions using 57 years of microdata on inflation expectations from the Reuters/Michigan Survey of Consumers. Differences in experiences strongly predict differences in expectations, including the substantial disagreement between young and old individuals in periods of highly volatile inflation, such as the 1970s. It also explains household borrowing and lending behavior, including the choice of mortgages.

It has become standard practice in the cross-sectional asset pricing literature to evaluate models based on how well they explain average returns on size-B/M portfolios, something many models seem to do remarkably well. In this paper, we review and critique the empirical methods used in the literature. We argue that asset pricing tests are often highly misleading, in the sense that apparently strong explanatory power (high cross-sectional R2s and small pricing errors) can provide quite weak support for a model. We offer a number of suggestions for improving empirical tests and evidence that several proposed models do not work as well as originally advertised.

We show that individuals’ macroeconomic expectations are influenced by their socioeconomic status (SES). People with higher income or higher education are more optimistic about future macroeconomic developments, including business conditions, the national unemployment rate, and stock market returns. The spread in beliefs between high- and low-SES individuals diminishes significantly during recessions. A comparison with professional forecasters and historical data reveals that the beliefs wedge reflects excessive pessimism on the part of low-SES individuals. SES-driven expectations help explain why higher-SES individuals are more inclined to invest in the stock market and more likely to consider purchasing homes, durable goods, or cars. Received November 13, 2017; editorial decision February 12, 2019 by Editor Wei Jiang.

To understand which short‐term debt markets experienced “runs” during the financial crisis, we analyze a novel data set of repurchase agreements (repo), that is, loans between nonbank cash lenders and dealer banks collateralized with securities. Consistent with a run, repo volume backed by private asset‐backed securities falls to near zero in the crisis. However, the reduction is only $182 billion, which is small relative to the stock of private asset‐backed securities as well as the contraction in asset‐backed commercial paper. While the repo contraction is small in aggregate, it disproportionately affected a few dealer banks.