Haowei (Wayne) Yuan

Using recent advances in network theory, we estimate the intra-industry connectedness for US publicly traded companies since the 1920s. We develop a stock-level composite centrality measure that captures multiple dimensions of a stock's interdependence with its industry peers. Using our network and composite centrality estimates, we develop "peer momentum" trading strategies, which sort stocks on their industry peers' past month average returns weighted by the peers' influence in the industry. A "peripheral peer momentum" (PPM) strategy that uses only peripheral stocks' influence for weighting in the signal construction achieves an annualized Sharpe ratio of approximately 0.62 and helps explain industry momentum. The predictability is driven by investor underreaction to peer-firm news, as evidenced by the concentration of PPM payoffs in the news component of the peer signal and among low-attention firms.

We investigate the real effects of equity mispricing on default probability and its implications for credit ratings accuracy. We find that equity overpricing significantly reduces the probability of default, primarily through increased investment and equity issuance. Examining methodological differences between Egan Jones Ratings (EJR) and Standard & Poor's (S&P), we show that EJR's quantitative approach makes its ratings more sensitive to equity mispricing compared to S&P's holistic method, particularly for financially distressed firms. Importantly, EJR's ratings demonstrate greater accuracy for both overpriced and underpriced firms. Our findings suggest that credit rating agencies employing quantitative models may better capture the effects of equity mispricing on default risk, thus improving rating accuracy. This study also highlights a previously unexplored real effect of equity mispricing on corporate defaults.

We uncover a fundamental divide in how asset pricing anomalies respond to shifts in investor risk sentiment: build-up anomalies thrive in risk-off periods while resolution anomalies collapse. Using momentum and value as representative cases, we show that value stocks and past losers experience sharp underperformance precisely when risk appetite deteriorates. Trading data offer an additional perspective: during risk-off episodes, retail investors flee value stocks, while short sellers double down, intensifying the drawdown. In contrast, momentum stocks evade similar selling pressure, reinforcing their resilience. Specifically, we distinguish between build-up and resolution anomalies, providing new evidence on the resilience of some anomalies in the face of deteriorating risk sentiment while others unravel. These differences in both returns and investor flows between anomaly types are difficult to coherently reconcile with a comprehensive theoretical explanation.

• “The professor was very well informed and was able to communicate the complex topics in a meaningful and impactful way. He was very patient with students' questions and very accommodating with commitments outside of the classroom.”
• “Professor Yuan has been a great resource for deepening my knowledge within finance. Overall, we learned multiple ways to valuate, analyze, and graph payoff/profit for derivatives such as options and futures through Excel.”
• “Professor Yuan was very open to providing additional help and always ensured that we understood how to complete the assignments.”
• “Professor is patient and willing to answer questions. I can get feedback real quick for each homework assignment.”