We propose a new method for constructing the hedge component in Merton's ICAPM that uses a daily summary measure of economic activity to track time-varying investment opportunities. We then use nonparametric projections to compute a robust estimate of the conditional covariance between stock market returns and our daily economic activity index. We find that the new conditional covariance risk measure plays an important role in explaining time variation in the equity risk premium. Specification tests as well as out-of-sample forecasts of aggregate stock returns suggest that the new covariance risk measure performs well compared to alternative covariance measures previously proposed in the literature.

We document a little-known source of information exploited by sophisticated institutional investors: the Freedom of Information Act (FOIA), a law that allows for the disclosure of previously unreleased information by the U.S. Government. Through FOIA requests, we identify several sophisticated institutional investors, chiefly hedge funds, that request information from the FDA. We explore the type of information commonly requested by funds and the types of firms that are targets of FDA-FOIA requests and show that FOIA requests allow these investors to generate abnormal returns. Thus, we illustrate a detailed mechanism through which costly information becomes incorporated into market prices.

We employ a novel brokerage account data set to investigate which individual investors are the most attentive, how investors allocate their attention, and the relation between investor attention and performance. Attention is positively related to investment performance, at both the portfolio return level and the individual trades level. We provide evidence that the superior performance of high-attention investors arises because they purchase attentiongrabbing stocks whose positive performance persists for up to six months. Finally, we show that paying attention is particularly profitable when trading stocks with high uncertainty, but for which a lot of public information is available. (

We propose a new method for constructing the hedge component in Merton's ICAPM that uses a daily summary measure of economic activity to track time-varying investment opportunities. We then use nonparametric projections to compute a robust estimate of the conditional covariance between stock market returns and our daily economic activity index. We find that the new conditional covariance risk measure plays an important role in explaining time variation in the equity risk premium. Specification tests as well as out-of-sample forecasts of aggregate stock returns suggest that the new covariance risk measure performs well compared to alternative covariance measures previously proposed in the literature.

We document four secular trends about U.S. mortgage origination by traditional and FinTech lenders after the 2008-2009 financial crisis. First, since 2011, the overall number, size, and approval rate of small and medium-sized loans have been decreasing over time, relative to large loans. Second, the largest lenders redistribute their lending the most. Third, this loan-size redistribution of credit increases in the size of the lender. Fourth, the effects are stronger for mortgages further away from the conforming loan limit(s) in both directions. We argue that the supply of credit drives these secular trends, and we assess several potential economic mechanisms.

We document a little-known source of information exploited by sophisticated institutional investors: the Freedom of Information Act (FOIA), a law that allows for the disclosure of previously unreleased information by the U.S. Government. Through FOIA requests, we identify several sophisticated institutional investors, chiefly hedge funds, that request information from the FDA. We explore the type of information commonly requested by funds and the types of firms that are targets of FDA-FOIA requests and show that FOIA requests allow these investors to generate abnormal returns. Thus, we illustrate a detailed mechanism through which costly information becomes incorporated into market prices. Received April 15, 2015; editorial decision April 16, 2016 by Editor Itay Goldstein.

We study the introduction of a wealth-management robo-adviser that constructs portfolios tailored to investors’ holdings and preferences. Adopters are similar to non-adopters in terms of demographics and prior interactions with human advisers but tend to be more active and have greater assets under management. Investors adopting robo-advising experience diversification benefits. Ex ante undiversified investors increase stock holdings and hold portfolios with less volatility and better returns. Already well-diversified investors hold fewer stocks, yet see some reduction in volatility, and trade more after adoption. All investors increase attention based on online account logins. We find that adopters exhibit declines in prominent behavioral biases, including the disposition, trend chasing, and rank effect. Our results emphasize the promises and pitfalls of robo-advising tools, which are becoming ubiquitous all over the world.Received May 31, 2017; editorial decision August 21, 2018 by Editor Wei Jiang.