Corporate bonds carry a premium of extreme illiquidity (EIL). This premium permeates all rating categories and heightens in times of stress and periods with high uncertainty. EIL has predictive power in the cross-section for future returns up to at least a one-year horizon. Active investors like...

This paper examines the relationship among daily information flow, return volatility, and bid-ask spreads based on the framework of the mixture of distribution hypothesis (MDH). The MDH model is modified to permit separate effects of informed and liquidity trading volume on return volatility....

We propose an alternative approach to the linear factor model to estimate and decompose asset risk premia in empirical asset pricing. To resolve the high-dimensional sort difficulty in forming characteristic-based benchmark portfolios, we introduce a benchmark combination model (BCM) that...

Using implied-CDS risk premium measures, we find that these variables have higher explanatory power for cross-sectional bond returns than the traditional default spread and ratings. The positive effect of the credit risk premium (CRP) factor on expected returns is pervasive, stronger for...

We document strong evidence of cross-sectional predictability of corporate bond returns based on a set of yield predictors that capture the information in the yields of past 1, 3, 6, 12, 24, 36 and 48 months. Return predictability is economically and statistically significant, and is robust to...

Using a robust textual analytic method, we decompose the P2P loan description into common and distinctive contents, which contain general and unique information provided by borrowers. We then investigate the role of the distinctive content in affecting P2P lending decisions and outcomes....

This paper documents substantial evidence of return predictability and investment gains for individual corporate bonds via machine learning. The forecast-implied long-short and market-timing strategies deliver significant risk-adjusted returns over transaction costs. Random Forest has the best...

This paper finds positive evidence of return predictability and investment gains for individual corporate bonds for an extended period from 1973 to 2017. Our sample consists of both public and private company bond observations. We have implemented multiple machine learning methods and designed a...