| Author: | Li, Nanqi |
| Title: | Two essays on empirical asset pricing |
| Advisors: | Wei, John (AF) Chen, Te-feng (AF) |
| Degree: | Ph.D. |
| Year: | 2025 |
| Department: | School of Accounting and Finance |
| Pages: | 125 pages : color illustrations |
| Language: | English |
| Abstract: | In the first chapter, we investigate the sources of prominent stock anomaly returns in the global markets by decomposing them into the cash flow news, the discount rate news, and the expected return components. Using analyst forecast data and the valuation model, we document that cash flow news is the primary contributor to anomaly returns across a broad spectrum of well-documented stock anomalies. While the variance of monthly returns for most anomalies is primarily explained by variation in discount rate news, the variance of their longer-term, annual returns tends to be increasingly dominated by variation in cash flow news. In addition, we find little support for the two-beta (CF and DR) model in accounting for the anomaly returns. Overall, the evidence demonstrates the role of investors’ dynamic expectations on firm fundamentals in driving prominent anomaly returns in the global markets. In the second chapter, we investigate the role of risk perceptions in risk premiums and asset prices. We argue that shifts in risk perceptions explain the time-varying nature of risk premiums, including those for prominent factors like size, profitability, and momentum. Using the Price of Volatile Stocks (PVS) as a measure of risk perception, we find significant in-sample and out-of-sample predictive power for various factor premiums. With Instrumented Principal Component Analysis (IPCA), we demonstrate how firms' observable characteristics, like asset-to-me value and past returns, expose individual stocks to risk perception. Stocks with higher PVS betas exhibit significantly lower future returns, indicating that risk perception is a priced factor in the cross-section. We construct a mimicking factor for PVS, confirming its significant negative risk price. Finally, through textual analysis with an LLM, we show how investors' expressed risk perceptions align with our quantitative findings, providing direct evidence of their impact on market dynamics and investment decisions. |
| Rights: | All rights reserved |
| Access: | open access |
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