Qiang Wang

In this paper, we investigate the impact of market sentiment on cryptocurrency returns. To accomplish this, we use a novel dataset that captures a multitude of attitudes, moods, and emotions extracted from a vast amount of news and social media content. Our findings indicate that social media sentiment significantly predicts crypto returns, while sentiment from news media does not. Additionally, we observe that fundamental events play a role in shaping sentiment, but market exuberance---sentiment unrelated to fundamental events---is a strong and robust predictor of returns. Furthermore, we find that market exuberance is positively related to momentum return but does not positively predict volatility. This suggests that sentiment influences returns through price perception and demand shocks rather than the risk premium channel. Overall, our research highlights the importance of sentiment in understanding and predicting cryptocurrency market dynamics. 

Blockchain-based decentralized Finance (DeFi) aims to promote financial inclusion by removing centralized intermediaries and providing direct services to users. This paper investigates whether Decentralized Financial (DeFi) lending markets, one of the largest DeFi applications, provide equal access. DeFi lending operates similarly to margin lending or repo transactions. Most borrowers use cryptocurrencies as collateral to borrow stablecoins, which are cryptocurrencies pegged to the US dollar. Using data at the account level, I find that highly leveraged borrowers who pledge low collateral relative to their loan amounts are constrained by collateral requirements. After platforms relax collateral requirements, highly leveraged borrowers increase borrowing and leverage further. Overall, this paper suggests that stringent collateral requirements in DeFi lending restrict access to borrowers who are already asset-rich.

Unexpected intercollegiate athletic success generates a variety of changes at universities -- including increased salience and status of sports-oriented activities among students, known colloquially as the "Cinderella effect". By linking data on athletic contest outcomes, betting lines, student debt default rates, and post-college earnings data, we find that Cinderella events disrupt human capital development among incumbent students and adversely affect their financial outcomes. Following such events, treated students exhibit higher default rates and lower earnings. This effect strengthens with treatment exposure (results are larger for freshmen than seniors) and is concentrated in low-ranked universities. These institutions show no changes in revenues or expenditures, suggesting that resource-driven explanations are unlikely to be the primary driver. In contrast, students at high-ranked universities have marginally lower default rates and higher earnings, as these schools receive more applications, increase selectivity, and have marginally higher revenues and expenditures. Overall, our results suggest that athletic success shifts students' preferences away from academic focus. More broadly, our results show that university environment affects human capital development, as distinct from selection effects that reflect assortive matching between students and universities.