Knowledge that Transforms

Higher initial margin requirements are associated with lower subsequent stock market volatility during normal and bull periods, but show no relationship during bear periods. Higher margins are also negatively related to the conditional mean of stock returns, apparently because they reduce systemic risk. We conclude that a prudential rule for setting margins (or other regulatory restrictions) is to lower them in sharply declining markets in order to enhance liquidity and avoid a depyramiding effect in stock prices, but subsequently raise them and keep them at the higher level in order to prevent a future pyramiding effect.

We model rational herd behavior when the underlying value changes over time, with pay-offs that are either dependent or independent of the underlying value. We show that herding does not last forever and is not monotone in signal quality. High correlation among agents' actions does not necessarily imply herding. This suggests alternative empirical methods are needed to detect herding. The model has many applications, including the IPO decision in which payoffs are state dependent. The model implies that the decision to go public is more likely associated with herding than the decision to delay an IPO.

Since liquidation and bankruptcy are costly, researchers have tried to find out why the claimants of a troubled firm do not work out a deal to avoid these costs. In this article we show that if a creditor has to deal with multiple borrowers who might default, it may be optimal for the creditor to randomly reject requests for a loan workout. We further demonstrate that the optimal acceptance rate used by a creditor is positively related to the liquidating cost and negatively related to the default benefit. Our model is particularly relevant when analyzing the default decisions of mortgage borrowers and small business owners.

The relationship between affine stochastic processes and bond pricing equations in exponential term structure models has been well established. We connect this result to the pricing of interest rate derivatives. If the term structure model is exponential affine, then there is a linkage between the bond pricing solution and the prices of many widely traded interest rate derivative securities. Our results apply to m-factor processes with n diffusions and I jump processes. The pricing solutions require at most a single numerical integral, making the model easy to implement. We discuss many options that yield solutions using the methods of the article.

This article studies the role of risk arbitrageurs in takeovers and the source of their advantage. We show how the presence of arbitrageurs affects the value of the target shares, since arbitrageurs are more likely to tender. Therefore an arbitrageur has the informational advantage of knowing he bought shares. In equilibrium, the number of arbitrageurs buying shares and the price they pay are determined endogenously. We also present several empirical implications, including the relationship among trading volume, takeover premium, liquidity of the shares, and the number of risk arbitrageurs investing in one particular deal.

This article examines whether country-specific or global versions of Fama and French's three-factor model better explain time-series variation in international stock returns. Regressions for portfolios and individual stocks indicate that domestic factor models explain much more time-series variation in returns and generally have lower pricing errors than the world factor model. In addition, decomposing the world factors into domestic and foreign components demonstrates that the addition of foreign factors to domestic models leads to less accurate in-sample and out-of-sample pricing. Practical applications of the three-factor model, such as cost of capital calculations and performance evaluations, are best performed on a country-specific basis.

This article studies momentum in stock returns, focusing on the role of industry, size, and book-to-market (B/M) factors. Size and B/M portfolios exhibit momentum as strong as that in individual stocks and industries. The size and B/M portfolios are well diversified, so momentum cannot be attributed to firm- or industry-specific returns. Further, industry, size, and B/M portfolios are negatively autocorrelated and cross-serially correlated over intermediate horizons. The evidence suggests that stocks covary "too strongly" with each other. I argue that excess covariance, not underreaction, explains momentum in the portfolios.

We study how decision-makers' concerns about robustness affect prices and quantities in a stochastic growth model. In the model economy, growth rates in technology are altered by infrequent large shocks and continuous small shocks. An investor observes movements in the technology level but cannot perfectly distinguish their sources. Instead the investor solves a signal extraction problem. We depart from most of the macro-economics and finance literature by presuming that the investor treats the specification of technology evolution as an approximation. To promote a decision rule that is robust to model misspecification, an investor acts as if a malevolent player threatens to perturb the actual data-generating process relative to his approximating model. We study how a concern about robustness alters asset prices. We show that the dynamic evolution of the risk-return trade-off is dominated by movements in the growth-state probabilities and that the evolution of the dividend-price ratio is driven primarily by the capital-technology ratio.