We examine the significance and uniqueness of individual-pair relationships cultivated through repeated loan interactions. Using a hand-collected dataset compiled of borrowing manager and loan officer information, we find that individual-pair relationship loans are associated with a cost-of-debt reduction of between seven to 13 basis points. We also document that the relationship has an economic impact even when other affiliations, for example, institutional pairs, social ties, cultural proximity, and gender, are considered. Individual-pair relationships matter because they furnish lenders with useful soft information, especially when the firm has a poor hard information environment or when the bank and loan officer rely less on hard information. In addition, we find that individual-pair relationship loans have fewer rating downgrades, suggesting that accumulated soft information leads to better loan quality. Collectively, our results highlight the unique value of sustained professional engagement between two individuals in the lending process.

In common-law systems, firms’ litigation risk depends both on written laws and how courts interpret these laws. Using 321 US circuit court rulings, we introduce a novel measure capturing courts’ attitudes toward defendants in securities lawsuits. Our results confirm that financial misreporting firms in more defendant-friendly circuits face fewer lawsuits. Consistent with lower expected litigation costs, firms in these circuits face less negative market reactions when misreporting is revealed, invest less in preventing misreporting, and are more likely to engage in aggressive misreporting. We conclude that defendant-friendly precedents reduce firms’ legal liability and worsen their financial reporting quality.

Disagreement measures are known to predict cross-sectional stock returns but fail to predict market returns. This paper proposes a partial least squares disagreement index by aggregating information across individual disagreement measures and shows that this index significantly predicts market returns both in- and out-of-sample. Consistent with the theory in Atmaz and Basak (2018), the disagreement index asymmetrically predicts market returns with greater power in high-sentiment periods, is positively associated with investor expectations of market returns, predicts market returns through a cash flow channel, and can explain the positive volume-volatility relationship.

We investigate whether and how an exogenous and unprecedented improvement in non-U.S. firms' financial-reporting quality affects post-earnings-announcement drift (PEAD). We find that PEAD declines after the information shock, and this decrease is more pronounced for firms with fewer concurrent earnings announcements, greater institutional holdings, and lower limits to arbitrage. In addition, the decrease in PEAD is driven by firms with greater changes in financial reporting, an increase in analyst forecast accuracy and institutional ownership, and a decrease in limits to arbitrage. These findings support the mispricing explanation of PEAD, in particular the limited attention hypothesis, in an international setting.

We develop a dynamic model of a platform economy where tokens serve as a means of payment among platform users and are issued to finance investment in platform productivity. Tokens are optimally rewarded to platform owners when token supply (normalized by productivity) is low and burnt to boost franchise value when the normalized supply is high. Although token price is determined in a liquid market, the platform’s financial constraint generates an endogenous token issuance cost that causes underinvestment through the conflict of interest between insiders (owners) and outsiders (users). Blockchain technology mitigates underinvestment by addressing the owners’ time inconsistency problem.

We propose a novel high-frequency decomposition of daily stock returns into news- and non-news-driven components, and uncover evidence of pervasive stock market underreaction to firm news. Prices tend to drift in the same direction as the initial market response for several days after the news arrival without reversals. A trading strategy exploiting the return drift generates high abnormal returns and remains profitable after transaction costs. To understand the economic mechanism, we find that the return drift is stronger when investors are distracted. Analysts’ slow adjustments of market expectations following firm news also contribute to the market underreaction.

We develop a dynamic asset pricing model of cryptocurrencies/tokens that allow users to conduct peer-to-peer transactions on digital platforms. The equilibrium price of tokens is determined by aggregating heterogeneous users’ transactional demand, rather than discounting cash flows as is done in standard valuations models. Endogenous platform adoption builds on user network externality and exhibits an -curve: it starts slow, becomes volatile, and eventually tapers off. The introduction of tokens lowers users’ transaction costs on the platform by allowing users to capitalize on platform growth. The resultant intertemporal feedback between user adoption and token price accelerates adoption and dampens user-base volatility.

This paper investigates whether top-tier M&A investment bankers (financial advisors) create value for acquirers with different financial conditions in both the short and long term via analyzing 3420 US deals during 1990–2012. In this paper, deals are divided into three groups based on acquirer financial constraints – acquisitions by constrained, neutral and unconstrained firms. We find that the effects of top-tier bankers are dependent on acquirer financial conditions. Specifically, top-tier advisors improve performance for constrained acquirers rather than neutral, and unconstrained acquirers. Our results show that top-tier investment bankers improve constrained acquirers’ short- (5 days) and long-term (36 months) performance by 1.45% and 24.27% respectively, after controlling for firm, deal and market characteristics. For deals with investment banker involvement, constrained acquirers advised by top-tier advisors have the lowest deal completion rate, and pay the lowest bid premiums; while unconstrained acquirers that retain top-tier investment bankers have the highest deal completion rate, and pay relatively high bid premiums. Our findings imply that constrained acquirers tend to retain top-tier investment bankers to gain superior synergy, while unconstrained acquirers appear to retain top-tier investment bankers to ensure the deal completion.

We find evidence consistent with previously unrecognized market manipulation by broker-dealers. Specifically, we show that pre-trade hedging, which is distinct from front-running, alters prices at which derivative trades occur. We show this behavior is intentional by exploiting variation in the design of structured equity products (SEPs). We find positive abnormal returns on SEP pricing dates for which issuers benefit from altering closing stock prices but no such returns on pricing dates of otherwise similar SEPs. We also show that large buy trades near the close of trading are more frequent when SEP issuers have incentives to alter closing stock prices.