Yu (William) Wang

“A threshold effect of COVID-19 risk on oil price returns”, Energy Economics, Volume 120, 2023, 106618, ISSN 0140-9883, with Yiguo Sun, Delong Li, and Chenyi Suo

Using U.S. data, we investigate how the COVID-19 pandemic influences oil price returns in an asset pricing framework. Unlike earlier studies, we consider a threshold model to allow for the possibility that COVID-19 risk may not play a role until it reaches a certain level. Based on WTI crude oil spot price data from January 2020 to December 2021, our findings show that oil returns significantly decline with the daily number of COVID-19 deaths but only if the daily death toll exceeds approximately 2100. In addition, a more severe COVID-19 pandemic can substantially increase the exposure of oil returns to various systematic risk factors, which has not been documented in previous literature.

1. Idiosyncratic contagion between ETFs and stocks: A high dimensional network perspective (Revise and resubmit at Journal of Financial Stability)

This paper employs high-dimensional vector autoregressive modelling and financial network analysis to explore return spillovers between ETFs and stocks. The study reveals important industry patterns in spillovers, with sectors like Utilities and Real Estate showing robust connections, while other sectors like Consumer Discretionary exhibit more external influences. The findings contribute to the literature by identifying previously overlooked spillover effects during periods of high market volatility.

2. Style rotation in ETFs: forecasting systematic risk factors with monetary and fiscal policy variables (Job market paper)

This paper focuses on style rotation in ETFs, where I apply a threshold regression model to predict market systematic risk factors based on shifts in monetary and fiscal policies. The predicted systematic risk factors are then used to construct a quarterly rebalanced portfolios of a pool of ETFs via a mean-variance optimization strategy. The study demonstrates that my proposed strategy generates excess returns that strongly correlate with changes in economic policy uncertainty, underscoring the model’s ability to capture key policy-driven threshold effects. 

Social Science and Humanity Research Council (SSHRC) Doctoral Award, 2024-2025