Knowledge that Transforms

In the Australian real estate market, about a third of properties are sold at auction. Properties that fail auctions sell later for a 1.3 percent discount. Consistent with a causal channel, the effect holds with property-level fixed effects and when auction failure is instrumented by adverse weather or seller overvaluation. Prices cluster below round numbers, and the discount fades over time, inconsistent with our effects reflecting unobserved property characteristics. The evidence suggests that there are behavioral factors affecting the valuations of buyers and sellers.

Many initial public offerings (IPOs) are priced at exactly the high-end of the pricing range. Investing in IPOs priced at the high-end leads to first-day returns that are substantially higher than investing in IPOs that are priced just below or above the high-end. We argue that these results are in line with issuing firms settling for positively perceived salient pricing points in negotiations with underwriters.

A theoretical model of the borrower–lender relationship predicts that increased competitive threats lead to a reduction in loan covenant restrictiveness that is stronger for groups of borrowers who face constraints to their ability to raise external financing or compete in the product market. These predictions arise because competition impacts the dynamics of borrower performance so that lenders must trade off the benefit of controlling agency problems against a heightened cost of lost product market opportunities for the borrower, ultimately lowering the optimal use of covenants. We find strong empirical support for these predictions, highlighting an important role of competition for optimal financial contracting rooted in underlying agency problems.

We combine high-frequency stock returns with risk-neutralization to extract the daily common component of tail risks perceived by investors in the cross-section of firms. Our tail risk measure significantly predicts the equity premium and variance risk premium at short horizons. Furthermore, a long–short portfolio built by sorting stocks on their recent exposure to tail risk generates abnormal returns with respect to standard factor models. Incorporating investors’ preferences via risk-neutralization is fundamental to our findings: the predictive power of the physical tail risk is weaker and generally subsumed by its risk-neutral counterpart.