Research Projects

(with Haitao Li, Xiaoxia Ye, and Fan Yu), scheduled for presentation at the 4th Contemporary Issues in Financial Markets and Banking conference, Jan. 2026.

Abstract

Government bond yields display pronounced non-Markov dynamics: moving averages of long-lagged yields substantially enhance the predictability of excess bond returns. To capture these features, we develop a systematic framework for constructing non-Markov Gaussian Dynamic Term Structure Models within the Heath–Jarrow–Morton setting. Compared with existing approaches, our framework is both more flexible and more parsimonious, enabling the estimation of economically meaningful non-Markov effects that improve forecasts of excess returns in-sample and out-of-sample. The models outperform traditional Markov specifications by more accurately capturing bond risk premiums, particularly through improved modelling of the conditional mean of risk factors. Most recent version

(with Xiaoxia Ye, Fan Yu, and Ran Zhao).

Abstract

We develop a broad set of asset-level measures of dealer network centrality for U.S. corporate bonds, explicitly incorporating dealer inventory management. We examine whether bonds traded by more central dealers earn higher mean excess returns and find that the resulting risk factors are fully spanned by the market. Our measures highlight the role of liquidity frictions in over-the-counter (OTC) bond trading and explain existing illiquidity metrics as they translate into bond-level credit spreads. Furthermore, using a variance decomposition model with expanded interdealer segments, we document that bonds traded by central dealers are more responsive to market-wide information transmission, underscoring the importance of OTC networks in corporate bond price formation.

(with Enrico Onali and Xiaoxia Ye).