We survey recent methodological contributions in asset pricing using factor models and
machine learning. We organize these results based on their primary objectives: estimating …

We show that the COVID-19 pandemic brought house price and rent declines in city centers,
and price and rent increases away from the center, thereby flattening the bid-rent curve in …

We perform a comparative analysis of machine learning methods for the canonical problem
of empirical asset pricing: measuring asset risk premiums. We demonstrate large economic …

The last 15 years has brought forth an explosion of research on consumption-based asset
pricing as a leading contender for explaining aggregate stock market behavior. This …

We formulate a dynamic no-arbitrage asset pricing model for equities and corporate bonds,
featuring time variation in both risk aversion and economic uncertainty. The joint dynamics …

We propose a new investor sentiment index that is aligned with the purpose of predicting the
aggregate stock market. By eliminating a common noise component in sentiment proxies …

We survey the literature on stock return forecasting, highlighting the challenges faced by
forecasters as well as strategies for improving return forecasts. We focus on US equity …

We apply the concept of carry, which has been studied almost exclusively in currency
markets, to any asset. A security's expected return is decomposed into its “carry,” an ex-ante …

This study examines the association between the level of the quality of integrated reporting
(IR) disclosure and a firm's market valuation. Employing data from IR firms during the years …

We investigate the impact of China's economic policy uncertainty (EPU) on the time series
variation of Chinese stock market expected returns. Using the news‐based measure of EPU …