We construct a novel panel data set to provide new evidence on how the largest nonfinancial firms manage their financial assets. Our granular data show that, over the past decade, bond portfolios have grown to be at least as large as cash-like instruments, driven by the meteoric rise of corporate bond holdings. To shed light on the drivers of this growth, we conduct a pair of event studies around the 2017 tax reform and the 2020 liquidity crisis. We find that large holdings of marketable securities are primarily driven by cross-border tax incentives, while cash-like instruments are driven by liquidity motives.

Information production is key to the efficiency of financial markets. Does selling information separately improve its production? We investigate this question using MiFID II, a European regulation that unbundles research from transactions. We show that unbundling causes fewer research analysts to cover a firm. This decrease does not come from small- or mid-cap firms but is concentrated in large firms. Surprisingly, the reduction in analyst coverage is accompanied by a decrease in forecast error. Further analyses suggest that analyst competition enhancement could drive the results: inaccurate analysts drop out, and analysts who stay produce more accurate research.

A common practice in the finance literature is to create characteristic portfolios by sorting on characteristics associated with average returns. We show that the resultant portfolios are likely to capture not only the priced risk associated with the characteristic but also unpriced risk. We develop a procedure to remove this unpriced risk using covariance information estimated from past returns. We apply our methodology to the five Fama-French characteristic portfolios. The squared Sharpe ratio of the optimal combination of the resultant characteristic-efficient portfolios is 2.13, compared with 1.17 for the original characteristic portfolios.