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Dissertation
Essays in Asset Pricing
2025
Overview
In chapter 1, we investigate the cross-sectional spillovers of earnings surprises and their implications for anomaly returns. By forming quarterly text embeddings derived from earnings call transcripts, we capture multifaceted relationships among public firms and effectively reflect shifts in their business focus. Employing these embeddings to project earnings surprises, we identify significant contemporaneous spillovers and a medium-term drift that persists for up to 20 days. One standard deviation increase in the projected earnings surprises induces a 3 basis points increase in the same-day return and about 2 basis points in the next day. Utilizing the predicted earnings surprise, we construct an aggregate factor capable of pricing a broad spectrum of market anomalies and demonstrating substantial forward-looking predictive power for prominent factors, including value and size.Chapter 2 introduces an innovative asset-pricing model designed to analyze the co-movement between stock and bitcoin returns within a dual-agent equilibrium framework. By weaving habit formation and fluctuating risk aversion into the fabric of this model, we enable an exploration of dynamic risk-sharing strategies between equity and cryptocurrency markets. Such an approach underscores the model's capacity to elucidate the empirical phenomena characterizing cryptocurrency markets, with a particular focus on the time-varying correlation with stock returns. Additionally, our model innovatively connects both the spot and futures prices of cryptocurrencies to these dynamic risk-sharing mechanisms, guided by crucial state variables that influence consumption patterns. Furthermore, the model delves into the covariance of returns and their association with both external and internal habit formation preferences, thereby offering new insights into the complexities of interactions within and between traditional and digital asset markets.
Publisher
ProQuest Dissertations & Theses
Subject
ISBN
9798265483560
