Abstract The trading of shares of the same firm in multiple markets has become common over the last 30 years, but there is little empirical evidence on the extent to which investors actively exploit multimarket environments. We introduce a volume-based measure of multimarket trading to address this question. Analyzing a large set of cross-listed firms, we find higher multimarket trading among markets with similar designs and strong enforcement of insider trading laws and for firms with higher institutional ownership. These findings are important for firms evaluating the benefits of cross listing and for markets competing for order flow.

We find that bond issues have substantially increased since the onset of the COVID-19 crisis in calendar week 12 (March 16-20) for bonds rated A or higher, but surprisingly also for bonds rated BBB or lower. In contrast to existing evidence on bond maturities in economic downturns, we document that maturities exceed those of bonds issued before by the same firms as well as the average maturities during normal times. Determinants of corporate bond spreads substantially differ between COVID-19 and normal times. Most prominently, asset tangibility has a highly significant negative effect on spreads during normal times. During COVID-19, this is reversed, especially in industries heavily affected by lockdown measures, reflecting the inflexibility associated with fixed assets. A different picture emerges for equity issues, which slowed considerably during the first 4 weeks of the pandemic, before accelerating again. Capital raised during COVID-19 via equity issues is approximately 5% of capital raised via bond issues.

The MiFID II regulation led to the unbundling of research and execution costs in Europe starting in 2018. We exploit the early adoption of an unbundling rule in Sweden in 2016 to provide evidence on the implications of unbundling for fund investors. Using a difference-in-differences framework and hand-collected data on bundled and unbundled commissions, we find no economically meaningful effect of unbundling on commissions. When we split the sample into more active and less active funds, we find that fund costs of more active funds increased in relative terms. Finally, we do not find evidence that the increased transparency of observing execution and research costs led to improved fund performance or information gains for investors’ fund selection process. Overall, our results suggest that investors did not significantly benefit from the unbundling of commissions.

We evaluate predictive regressions that explicitly consider the time-variation of coefficients in a comprehensive Bayesian framework. For monthly returns of the S&P 500 index, we demonstrate statistical as well as economic evidence of out-of-sample predictability: relative to an investor using the historic mean, an investor using our methodology could have earned consistently positive utility gains (between 1.8% and 5.8% per year over different time periods). We also find that predictive models with constant coefficients are dominated by models with time-varying coefficients. Finally, we show a strong link between out-of-sample predictability and the business cycle.

Abstract We analyze the profitability of government-owned banks’ lending to their owners, using a unique data set of relatively homogeneous government-owned banks; the banks are all owned by similarly structured local governments in a single country. Making use of a natural experiment that altered the regulatory and competitive environment, we find evidence that such lending was used to transfer revenues from the banks to the governments. Some of the evidence is particularly pronounced in localities where the incumbent politicians face significant competition for reelection.

Abstract Previous work shows large differences in fees for S&P 500 index funds and other funds and suggests that investors suffer wealth losses investing in high-fee funds when similar low-fee funds are available. In contrast, the neoclassical model of mutual funds (Berk and van Binsbergen, 2015, J. Financ. Econ., 118, 1–20) argues that percentage fees are irrelevant, as fund size will adjust in equilibrium such that net alphas are equal to zero. We show that fees matter from an investor perspective. We document (i) a strong negative association between net-of-fee fund performance and fees in a sample of all US and international equity funds, (ii) economically large, robust, persistent, and pervasive fee dispersion in the mutual fund industry, and (iii) important economic effects for investors. During the sample period, the mutual fund industry has generated a total value lost (i.e., a negative net value added) of 125 billion USD, coming predominantly from high-fee funds.

Surprisingly little is known about the business cycle dynamics of leverage. The existing evidence documents that target leverage evolves pro-cyclically either for all firms or financially constrained ones. In contrast, we show that, on average, target leverage ratios evolve counter-cyclically once cyclicality is measured comprehensively, accounting for variation in explanatory variables and model parameters. These counter-cyclical dynamics are robust to different subsamples of firms, data samples, empirical models of leverage, and definitions of leverage. There is a fraction of 10–25% of firms with pro-cyclical dynamics whose characteristics are consistent with counter-cyclical dynamics for loss-given-default and probability of default.

ABSTRACT We examine the pricing of both aggregate jump and volatility risk in the cross‐section of stock returns by constructing investable option trading strategies that load on one factor but are orthogonal to the other. Both aggregate jump and volatility risk help explain variation in expected returns. Consistent with theory, stocks with high sensitivities to jump and volatility risk have low expected returns. Both can be measured separately and are important economically, with a two‐standard‐deviation increase in jump (volatility) factor loadings associated with a 3.5% to 5.1% (2.7% to 2.9%) drop in expected annual stock returns.