New book: Machine Learning in Asset Pricing (Princeton University Press). Expanded version of my Princeton Lectures in Finance in May 2019. Book coming out in May 2021. Now available for pre-order on Amazon
New paper: Market Efficiency in the Age of Big Data with Ian Martin. We put Bayesian investors into a high-dimensional environment in which they have to learn how to predict cash flows with a large number of potential predictors. Asset returns will exhibit in-sample cross-sectional return predictability even though returns are not predictable out-of-sample.
NBER Panel on Future of Asset Pricing: A link to a short write-up of my remarks on models of beliefs in asset pricing at an NBER Panel Nov. 8, 2019.
I recently gave the Princeton Lectures in Finance, on Asset Pricing and Machine Learning: Slides are available here
Now forthcoming in the RFS: Bank Risk Dynamics and Distance to Default
with Amiyatosh Purnanandam.
Now forthcoming in the RFS: Socioeconomic Status and Macroeconomic Expectations, with Sreyoshi Das and Camelia Kuhnen.
New paper: Do Survey Expectations of Stock Returns Reflect Risk-Adjustments? with Klaus Adam and Dmitry Matveev. We reject the hypothesis that survey expectations of returns reflect risk-adjustments or marginal utility weighting (e.g., risk-neutral expectations). Theories of risk-adjusted survey expectations therefore do not help to reconcile survey expectations with expected returns implied by rational expectations asset-pricing models and return predictability regressions.
New paper: Judging Bank Risk by the Profits They Report, with Ben Meiselman and Amiyatosh Purnanandam. We show that high rates of bank profitability (ROA, ROE) in good times are predictors of systematic tail risk exposure in bad times—just like the yield of a risky bond portfolio in good times tends to be an indicator of systematic tail risk exposure.
New paper: Socioeconomic Status and Macroeconomic Expectations, with Sreyoshi Das and Camelia Kuhnen. We show that individuals of lower socioeconomic status (SES) have more pessimistic macroeconomic expectations. Helps explain, e.g., lower rates of stock market participation among low-SES individuals. The beliefs wedge between low- and high-SES individuals shrinks in recessions, consistent with a model in which low-SES individuals neglect good (macroeconomic) states of the world.
New paper: Shrinking the Cross-Section, with Serhiy Kozak and Shrihari Santosh. We use SDFs to summarize the cross-section of expected stock returns in a high-dimensional setting with a huge number of characteristics and their interactions. Uses tools from machine learning combined with economically motivated objective functions.