Adding a size-discovery trading protocol, where a break in the limit order book occurs to match orders at a fixed price, can increase allocative efficiency in markets with slow trading frequency. A high trading frequency spreads liquidity, resulting in a strong incentive to wait for a size-discovery session. This incentive to delay trade is smaller in slower markets, and its negative effect on efficiency can be offset in slower markets by the positive effect of size discovery. This result rationalizes the empirical fact that size-discovery protocols only exist in slower markets. Potential conflicts of interest between traders and platform operators are identified but seem unlikely to drive the existence of size-discovery trading protocols.

We develop a structural empirical framework to study voting outcomes and the role of proxy advisors for shareholder proposals. Voting errors occur when bad proposals pass (false positives) and good proposals fail (false negatives). 6.5% of voting outcomes for shareholder proposals are mistakes, the majority being false positives. Recommendations by proxy advisor ISS are incorrect roughly half the time. ISS makes more mistakes when they support proposals (70%), but investors rely less on those recommendations than when ISS is not in favor. Errors in voting outcomes are more sensitive to proxy advisor informativeness and influence than to proposal quality.

Detecting informed trade by corporate insiders is costly and is the subject of significant regulatory and market scrutiny. We introduce a mixture model that leverages the cross-section of insiders' past returns to infer which insiders are more likely to engage in informed trade. The estimation explicitly accounts for the noisiness of insiders' performance histories. Out-of-sample returns are higher for stocks traded by insiders identified as more likely to use information, and prices reflect this information faster over the last decade. The model for insiders implies a person-specific mixture distribution that can be used to classify whether any disclosed trade is informed.

Are daily market closures still needed? In a model of large traders who manage inventory risk, we show that traders engage in aggressive trading in anticipation of even a short market closure, which coordinates and concentrates liquidity. A market structure with a daily closure improves allocative efficiency relative to a continuously open market, even though traders cannot trade during the closure itself. If traders have heterogeneous information about the asset value, trade is less aggressive on the whole, but closure still retains its substantial welfare benefits. A calibration of our model suggests moving to longer, say 23/7, trading hours would be beneficial, but moving to 24/7 trading would harm welfare.