Abstract We construct a traded funding liquidity measure from stock returns. Guided by a model, we extract the measure as the return spread between two beta-neutral portfolios constructed using stocks with high and low margins, to control for their sensitivity to the aggregate funding shocks. Our measure of funding liquidity is correlated with other funding liquidity proxies. It delivers a positive risk premium that cannot be explained by existing risk factors. A model augmented by our funding liquidity measure has superior pricing performance for various portfolios. Despite evident comovement, this measure contains additional information that is not subsumed by market liquidity. Received March 29, 2017; accepted August 8, 2018 by Editor Wayne Ferson.

Abstract In contrast to past studies that assume service flow of durable goods consumption to be a constant fraction of the stock, we study a consumption-based asset pricing model featuring time-varying utilization of durable goods. We propose an innovative measure of the unobserved usage of durable goods from carbon dioxide emissions. We find that the time-varying utilization of durable goods is a valid pricing factor. Our model exhibits a stronger cross-sectional pricing power than several consumption-based capital asset pricing models, including Yogo’s (2006) durable goods model. Finally, our model mitigates the joint risk premium and implied risk-free rate puzzle.

We evaluate the performance of various methods for estimating factor returns in an approximate factor model. Differences across estimators are most pronounced when there is cross-sectional heteroscedasticity or when cross-sectional sample sizes, n, have fewer than 4,000 assets. Estimators incorporating either cross-sectional or time-series heteroscedasticity outperform the other estimators when those types of heteroscedasticity are present. The differences are most pronounced when the cross-sectional sample is small. Received December 2, 2015; editorial decision May 16, 2017 by Editor Jeffrey Pontiff.

The upsurge of shadow banking is typically driven by rising financing demand from certain real sectors. In China, the 4 trillion yuan stimulus package in 2009 was behind the rapid growth of shadow banking after 2012, expediting the development of Chinese corporate bond markets in the poststimulus period. Chinese local governments financed the stimulus through bank loans in 2009 and then resorted to nonbank debt financing after 2012 when faced with rollover pressure from bank debt coming due. Cross-sectionally, using a political-economy-based instrument, we show that provinces with greater bank loan growth in 2009 experienced more municipal corporate bond issuance during 2012–2015, together with more shadow banking activities including trustloans and wealth management products. China’s poststimulus experience exhibits similarities to financial market development during the US National Banking Era.

Abstract Previous research has revealed that return spreads between stocks with high and low characteristics-based factor beta remain insignificant. This study investigates the time variation in the pricing of various characteristics-based factors, uncovering a notable two-regime pattern: high-beta portfolios yield higher returns than low-beta portfolios after high-sentiment periods, while the opposite occurs after low-sentiment periods. Remarkably, this two-regime pattern is completely reversed for macro factors. Mutual fund and hedge fund returns corroborate these findings. Our results suggest that exposure to characteristics-based factors likely represents mispricing levels, particularly during high-sentiment periods, whereas exposure to macro factors likely represents risk, particularly during low-sentiment periods.