Research

Working Papers

Managerial Expected Growth and The Value Premium (Job Market Paper)

• Abstract:  This paper introduces Managerial Expected Growth (MEG), a firm-level measure of expected growth extracted from the forward-looking statements of 10-K and 10-Q MD&As via supervised text learning, without using market prices and analysts' forecast. MEG predicts firm's future growth after controlling conventional growth proxies, such as book-to-market and other relevant firm characteristics. Cross-sectionally, high-MEG firms, those with high disclosed growth prospects, earn lower premium: a value-weighted low-minus-high MEG strategy earns 0.55% per month over 2000--2024 (FF4 alpha 0.73%, t = 3.71). High-MEG firms resemble growth-option-rich firms with increasing intangible investment, lower profitability, and lottery-like payoffs. I provide evidence that this value premium is not attributable to correction of biased expectations or limits to arbitrage, as suggested by the prior literature.

• Presentations:  3rd AI in Finance 2026 (Scheduled), 2026 AFA PhD Poster Session, 2025 FMA, 2025 FMA Doctorial Consortia, PSU Colloquium (2025)

• Grants & Awards: Smeal Small Research Grant ($1500)

Peer Momentum  (with Mihail Velikov, Ulas Misirli, and Daniela Scidá)

• Revise and Resubmit at Review of Finance

• Abstract:  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.

• Presentations:  CMU-Pitt-PSU Finance Conference, Eastern FA (2022), D.C. Area Juniors Finance Conference (2022), International Association for Applied Econometrics Conference (2022)

Mispriced Equity, Default Likelihood, and Credit Rating Accuracy (with Alexei Zhdanov and Samuel Bonsall IV)

• Reject and Resubmit at Journal of Accounting and Economics

• Abstract:  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.

• Presentations:  PSU Seminar(2024)

A Tale of Two Anomalies: Value, Momentum, and Risk Sentiment (with Christian Lundblad, Mihail Velikov, and Alexei Zhdanov)

• Abstract:  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.

• Presentations: PSU Brownbag* (2024); 19th International Behaviour Finance Conference (2025); EasternFA (2026)

Work in Progress