We build a model of universities combining their real production decisions with their choice of endowment size and asset allocation. Variation in opportunity cost, that is, the productivity of internal projects, has a first-order effect on these choices. Adding the UPMIFA-mandated 7% payout constraint, the endowment size and asset allocations match those empirically observed. This constraint has little effect on universities that do not value the output of their internal projects but harms those that do: it prevents the endowment's use as an effective buffer stock, thereby increasing the volatility of production, and it slows the growth of the most productive universities.

We model how firms releasing information on different dates causes the CAPM to fail, requiring an additional factor based on the information structure to price assets. We exemplify this mechanism’s empirical relevance using quarterly earnings announcements, which cluster across months along size and book-to-market. Seventy percent of the alpha reduction from including SMB and HML occurs in the four main earnings announcement months. The information structure factor accounts for all of SMB and HML’s seasonal alpha reduction and one third of their overall alpha reduction. Controlling for size and book-to-market, exposures to SMB and HML vary with firms’ earnings announcement month.

A stock’s market exposure, beta, varies across return frequencies. Sorting stocks on the difference between low- and high-frequency betas (Δβ) yields large systematic mispricings relative to the CAPM at high frequencies, but significantly smaller mispricings at low frequencies. We provide a risk-based explanation for this frequency dependence by introducing uncertainty about the effect of systematic news on firm value (opacity) into a frictionless model. We document a robust relationship between the frequency dependence of betas and proxies for opacity. Our findings suggest that opacity poses significant challenges to using betas estimated from high-frequency returns. While the CAPM may be an appropriate asset pricing model at low frequencies, additional factors, e.g., based on opacity, are necessary at high frequencies. (JEL G11, G12, G13, G14)

ABSTRACT U.S. industrial firms invest heavily in noncash, risky financial assets such as corporate debt, equity, and mortgage‐backed securities. Risky assets represent 40% of firms’ financial portfolios, or 6% of total book assets. We present a formal model to assess the optimality of this behavior. Consistent with the model, risky assets are concentrated in financially unconstrained firms holding large financial portfolios, are held by poorly governed firms, and are discounted by 13% to 22% compared to safe assets. We conclude that this activity represents an unregulated asset management industry of more than $1.5 trillion, questioning the traditional boundaries of nonfinancial firms.