By buying convertibles and shorting the underlying stock, hedge funds distribute equity exposure to well-diversified shareholders. We find that firms with characteristics that make seasoned equity offerings expensive are more likely to issue convertibles to hedge funds. We conclude that hedge funds provide opportunities for firms to issue convertible securities at a lower cost than seasoned equity by serving as relatively low-cost distributors of equity exposure. A higher fraction of a convertible is privately placed with hedge funds when institutional ownership, stock liquidity, issue size, concurrent stock repurchases, and limitations on callability suggest that shorting costs will be lower.

We examine the effects of price disclosure on market performance in a continuous experimental multiple-dealer market in which seven professional market makers trade a single security. The dealers trade with one another and with computerized informed and liquidity traders. Our key comparison is between fully public price queues (pretrade transparent market) and bilateral quoting (pretrade opaque). We find that opening spreads are wider and trading volume is lower in the opaque markets due to higher search costs there. More importantly, however, higher search costs also induce more aggressive pricing strategies, so that price discovery is much faster in the opaque markets.

We investigate the information contained in foreign exchange (FX) volume using a novel data set from the over-the-counter market. We find volume helps predict next-day currency returns and is economically valuable for currency investors. Predictability implies a stronger return reversal for currency pairs with abnormally low volume and is driven by the component of volume unrelated to volatility, liquidity, and order flow. We rationalize these findings via a simple model, in which FX volume helps reveal the degree of asymmetric information in currency markets. Testing this prediction shows that asymmetric information is uniform across currency pairs but varies across instruments.

We investigate how transaction costs change the number of characteristics that are jointly significant for an investor’s optimal portfolio and, hence, how they change the dimension of the cross-section of stock returns. We find that transaction costs increase the number of significant characteristics from 6 to 15. The explanation is that, as we show theoretically and empirically, combining characteristics reduces transaction costs because the trades in the underlying stocks required to rebalance different characteristics often cancel out. Thus, transaction costs provide an economic rationale for considering a larger number of characteristics than that in prominent asset-pricing models.

This paper challenges the widely accepted stylized fact that chief executive officers (CEOs) in the United States are paid significantly more than their foreign counterparts. Using CEO pay data across fourteen countries with mandated pay disclosures, we show that the U.S. pay premium is economically modest and primarily reflects the performance-based pay demanded by institutional shareholders and independent boards. Indeed, we find no significant difference in either level of CEO pay or the use of equity-based pay between U.S. and non-U.S. firms exposed to international and U.S. capital, product, and labor markets. We also show that U.S. and non-U.S. CEO pay has largely converged in the 2000s.

The field of asset pricing is a rich and diverse discipline that has contributed to many areas of discourse, including those of fundamental importance to policy makers, investors, and households.1 As we look ahead during a time of substantial economic and political change, it is apparent that society faces many pressing questions, both new and old, that the field is uniquely suited to informing.To contribute to this conversation, the NBER Asset Pricing program convened a panel discussion on “Perspectives on the Future of Asset Pricing” at its November 8, 2019, meeting that took place at Stanford University. The objective of the panel was to identify some of the important questions the field could productively address in the next five to 10 years. The panelists, consisting of experts in several subfields of asset pricing, were invited to share their views on these questions with an eye toward innovative research topics that are ripe for exploring, and the metrics the field could be using to gauge progress.

We analyze the computational reproducibility of more than 1,000 empirical answers to 6 research questions in finance provided by 168 research teams. Running the researchers’ code on the same raw data regenerates exactly the same results only 52% of the time. Reproducibility is higher for researchers with better coding skills and those exerting more effort. It is lower for more technical research questions, more complex code, and results lying in the tails of the distribution. Researchers exhibit overconfidence when assessing the reproducibility of their own research. We provide guidelines for finance researchers and discuss implementable reproducibility policies for academic journals.