We propose a new asset-pricing framework in which all securities' signals are used to predict each individual return. While the literature focuses on each security's own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes...

We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no arbitrage restrictions by regularizing appropriate groups of coefficients. The second...

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...

This paper constructs risk-free interest rates implicit in index option prices for ten of the major G11 currencies. We compare these rates to the yields of government bonds to provide international estimates of the convenience yield earned by safe assets. Average convenience yields across...

This paper investigates the market pricing of subprime mortgage risk on the basis of data for the ABX.HE family of indices, which have become a key barometer of mortgage market conditions during the recent financial crisis. After an introduction into ABX index mechanics and a discussion of...

Hedge funds significantly reduced their equity holdings during the recent financial crisis. In 2008Q3-Q4, hedge funds sold about 29% of their aggregate portfolio. Redemptions and margin calls were the primary drivers of selloffs. Consistent with forced deleveraging, the selloffs took place in...

Using only daily data on bond and stock returns, we identify and characterize flight to safety (FTS) episodes for 23 countries. On average, FTS days comprise less than 3% of the sample, and bond returns exceed equity returns by 2.5 to 4%. The majority of FTS events are country-specific not...

This paper uses a dataset of more than 900,000 news stories to test whether news can predict stock returns. We measure sentiment with a proprietary Thomson-Reuters neural network. We find that daily news predicts stock returns for only 1 to 2 days, confirming previous research. Weekly news,...

During the COVID-19 market crash, U.S. stocks with higher institutional ownership -- in particular, those held more by active, short-term, and more exposed institutions -- performed worse. Portfolio changes through the first quarter of 2020 reveal that institutional investors prioritized...