Abstract: A factor using an earnings measure treating intangible and physical investments symmetrically represents “quality.” It has smaller left tail risk and co-tail risk with the market than does RMW of Fama and French (2015) and has lower down-market than up-market exposure. Our factor has significant alpha relative to many extant multi-factor asset-pricing models, including the Fama-French model (α = 2.9%). Its performance is due to superior asset selection (market timing) on the long (short) side. When the profitability factor in the Fama-French model is replaced with our factor the resulting model performs better in explaining both the cross section of stock returns and several extant anomalies.
Discussant: Sebastien Betermier, McGill University
Abstract: We study how noise trading flows impact the cross-section of asset prices in a market where sophisticated investors enforce no-arbitrage. In our model, individual asset flows, aggregated at the factor level, drive fluctuations in factor risk premia, which in turn impact asset prices through beta pricing. This structure fits the reduced-form patterns of how each asset’s flow impacts its own price and other assets’ prices with only a few factor-level parameters. A model-implied trading strategy, designed to exploit the reversion of factor-level price impacts, delivers strong investment outcomes and improves the performance of a wide range of anomaly portfolios.
Abstract: We test a model for the cross-section of corporate bond returns rooted in axiomatic preference theory. Preferences with disappointment aversion embedded in an intertemporal asset pricing framework with time-varying macroeconomic uncertainty imply a linear factor representation for expected returns. Besides the market and volatility factors, downside risk and its interactions with market and volatility risk represent three additional priced risks. Our findings strongly support the model when tested at the individual bond level, with robust evidence across alternative specifications and against the inclusion of empirically motivated factors. The model also significantly outperforms the bond CAPM for most test portfolios.
Discussant: Johnathan Loudis, University of Notre Dame
