We show that corporate bond returns are well-explained by a conditional factor pricing model. [SSRN]
Instrumented Principal Component Analysis (WP) w/ Kelly and Su
Factor estimation using instrumental data to capture both cross-sectional and time-series variation in factor loadings [SSRN]
Earnings Risk in the Household: Evidence from Millions of U.S. Tax Returns (AERI 2020) w/ Turner
Households experience less earnings risk than primary earners alone, because of intra-household insurance along the intensive and extensive margins. [publication] [SSRN]
Characteristics are Covariances: A Unified Model of Risk and Return (JFE 2019) w/ Kelly and Su
Stock characteristics are connected to expected returns because they tell us about covariance with aggregate factors. [publication] [SSRN]
Understanding Momentum and Reversal (JFE forth) w/ Kelly and Moskowitz
We show that the momentum and long-term reversal effects are explained by a conditional factor pricing model. [SSRN]
Estimating Monetary Policy Rules When Nominal Interest Rates Are Stuck at Zero (JMCB 2017) w/ Kim
With the onset of the ZLB, we find a decrease in the perceived monetary policy response to inflation, using surveys of professional forecasts to sidestep data censorship. [publication] [SSRN]
The Liquidity Effects of Official Bond Market Intervention (JFQA 2018) w/ DePooter and Martin
We find significant liquidity effects to ECB sovereign bond purchases, using a search-based asset pricing model to understand the mechanism. [publication] [SSRN]
Systemic Risk and the Macroeconomy: An Empirical Evaluation (JFE 2016) w/ Giglio and Kelly
We evaluate a wide array of systemic risk indicators and their ability to forecast the quantiles of real activity, and propose methods for combining them that show there is a latent systemic risk factor that is robustly related to future macroeconomic downside risk. [publication] [SSRN]
The Three-Pass Regression Filter: A New Approach to Forecasting Using Many Predictors (JoE 2015) w/ Kelly
The 3PRF is a simple least squares forecaster using many predictor variables that directly estimates the relevant forecast factors and is asymptotically normal for the best possible forecast. [publication] [SSRN]
The Demand for Youth: Explaining Age Differences in the Volatility of Hours (AER 2013) w/ Jaimovich and Siu
Young workers' hours and wages are more cyclically volatile than prime-aged workers' and a successful explanation of these facts comes from differential demand for young and prime-aged labor. [publication] [draft]
