We investigate the return predictability of corporate bonds using big data and machine
learning. We find that machine learning models substantially improve the out-of-sample …

Long-term reversals in corporate bonds are economically and statistically significant in a
comprehensive sample spanning the period 1977 to 2017. Such reversals are stronger for …

We decompose the accrual premium and study its components in the debt and equity
markets. We show that the importance of each accrual component depends on the sample …

This paper shows empirically that mutual funds, facing fund flow risk and liquidity risk,
significantly distort expected corporate bond returns due to their distinct asset demands as …

Reaching for yield, which we define as an investor preference for higher-yield bonds at a
given rating or for higher-rated bonds at given yields, is associated with inflated valuation …

There is a pervasive inverse relationship between corporate asset growth rates and bond
performance. Lower performance of bonds issued by high-asset growth firms may be the …

This paper introduces a factor based on an estimated probability of bankruptcy—a measure
of the risk a typical investor will lose their investment, or the cost of insuring that investment …

This dissertation consists of three essays. Chapter 1 is titled “Calibration for multivariate
bilateral gamma model”. In this chapter, we discuss the multivariate bilateral gamma (MBG) …

In the first chapter, I investigate the effects of private information in determining price
momentum, as measured by the probability of informed trading (PIN). Leveraging recent …

This dissertation studies the cross-section of asset returns. That is, why do certain assets
receive higher average returns than others and what factors drive these differences in …