We develop an equilibrium model in a 2-country, 2-good, pure exchange economy in which investors with logarithmic utility functions have heterogeneous beliefs about exogenously given output or endowment processes. We obtain closed-form representations of real exchange rates and of stock prices. We show that heterogeneous beliefs together with heterogeneous preferences make the volatility of real exchange rates and of stocks exhibit some properties that have been well documented in the empirical literature. These properties include the high volatility of both real exchange rates and stocks compared with that of economic fundamentals, the high correlation of stocks during periods of volatile markets. The model can also generate the clustering of the volatility of foreign exchange rates and stocks if the differences of beliefs are clustering.

There is a large and growing literature on how to model the dynamics of the default-free term structure to fit the observed historical data. Much less is known about how best to model the dynamics of defaultable yield curves. This paper develops a class of defaultable term structure models that is tractable enough to be empirically implemented and flexible enough to capture some important behaviors of the credit spreads in the data. We compare two non-nested models within this class using a Bayesian estimation technique, which helps to solve the problem of latent state variables. The Bayesian approach also enables us to test the two non-nested models on the basis of the Bayes factor. The results strongly suggest that models with constant transition probabilities will not be able to fit the observed dynamics of inter-rating spreads.

Following the global financial crisis, banks lengthened the average maturity of their assets relative to that of their liabilities, principally by increasing their investments in mortgage-related assets. Whether such maturity transformation exposes banks to interest rate risk depends, in part, on the effectiveness of bank deposits as a hedge against interest rate shocks. In this paper we provide evidence that interest pass-through rates on deposits vary significantly with interest rates, which reduces the effectiveness of deposits as a hedge when interest rates increase. The dynamic nature of the deposit betas explains, in part, why the duration of bank equity varies with interest rates and why interest rate risk models need to account for how pass-through rates vary with interest rates.

There are two major institutional investors in the syndicated loan market: collateralized loan obligations (CLOs) and loan mutual funds. CLOs are closed-end funds while loan funds are open-end funds that issue claims that are redeemable on demand. In this paper, we examine whether CLOs provide arbitrage capital that contributes to the resilience of loan funds. We find that CLOs act as shock absorbers, providing liquidity through par-building trades when loan funds experience large outflows. However, CLO-provided liquidity is limited to par build–eligible loans, leading to potential flow-induced fire sales among par build–ineligible loans. (JEL G23, G38

We present the first comprehensive study of mutual fund voting in proxy contests. Among contests where voting takes place, passive funds are 10 percentage points less likely than active funds to vote for dissidents. The gap shrinks significantly when accounting for votes withheld from management nominees, settled contests, and votes by non-“Big-Three” fund families. Passive and active funds are equally informed about firm fundamentals, although passive funds view contest-related SEC filings more often than active funds during contests, in absolute levels and incrementally relative to noncontest periods. We conclude that passive funds are engaged shareholders in high-stakes voting events.

Decentralized autonomous organizations (DAOs) have emerged as a new organizational structure that leverages smart contracts and blockchain technology. Academics and practitioners have paid significant attention to DAOs, yet DAO decision-making processes and the broader implications remain under-studied. This paper aims to fill this gap in the literature. First, we compare the proposal- and voting-based governance mechanisms of DAOs with those of traditional corporate governance. Second, we introduce various novel voting models adopted by DAOs. Third, we discuss DAOs' drawbacks and highlight a unique agency problem arising from large token holders, termed “whales,” within these organizations. The concentrated ownership such whales, whose interests may diverge from those of smaller token holders (i.e., users), obtain can result in governance vulnerabilities. After discussing recent instances of investor activism and contentious votes involving DAOs, we conclude by surveying the literature on the optimal DAO design.

We document numerous occurrences of pump-and-dump schemes (P&Ds) targeting cryptocurrencies, which tend to trigger short-term episodes that feature dramatic increases in prices, volume, and volatility, followed by quick reversals. The evidence we document, including price run-ups before P&Ds start, suggests wealth transfers from outsiders to insiders. Our findings based on wallet-level data are consistent with the reasoning that gambling preferences, overconfidence, and naïve reinforcement learning help explain P&D participation. Finally, exploiting two natural experiments in which exchanges altered P&D policies, we find evidence consistent with the idea that P&Ds contribute to reduced cryptocurrency liquidity and lower prices.

We propose and estimate a model of endogenous informed trading that is a hybrid of the PIN and Kyle models. When an informed trader trades optimally, both returns and order flows are needed to identify information asymmetry parameters. Empirical relationships between parameter estimates and price impacts and between parameter estimates and stochastic volatility are consistent with theory. We illustrate how the estimates can be used to detect information events in the time series and to characterize the information content of prices in the cross-section. We also compare the estimates to those from other models on various criteria. Received April 5, 2017; editorial decision September 21, 2017 by Editor Itay Goldstein.

We estimate institutional investor preferences from proxy voting records. The W-NOMINATE method maps investors onto a left-right dimension based on votes for fiscal year 2012. Public pension funds and other investors on the left support a more social and environment-friendly orientation of the firm and fewer executive compensation proposals. “Money-conscious” investors appear on the right. The proxy advisor ISS makes voting recommendations that place it center, to the left of most large mutual funds. A second dimension reflects a more traditional governance view, with management-disciplinarian investors, the proxy advisor Glass Lewis among them, pitted against more management-friendly ones.

A number of sell-side healthcare analysts gain access to information outside the purview of management through Freedom of Information Act requests to the Food and Drug Administration for records on factory inspections, complaints, and drug and medical device applications. Using a difference-in-differences methodology, we find that buy (sell) recommendations and upgrades (downgrades) earn higher (lower) stock returns over the year following the receipt of FDA records. We also examine the type of information revealed in FDA factory inspection reports, and find that analysts are less likely to downgrade and are less pessimistic in their recommendations than the consensus recommendation when the information contained in the FDA report is not particularly severe. Our findings are consistent with a subset of analysts utilizing non-public information channels independent of management to gain value-relevant information about their covered firms.