Knowledge that Transforms

We study market efficiency in an infinite-horizon model with a monopolistic insider. The insider can trade with a competitive market maker and noise traders, and observes privately the expected growth rate of asset dividends. In the absence of the insider, this information would be reflected in prices only after a long series of dividend observations. The insider chooses, however, to reveal the information very quickly, within a time converging to zero as the market approaches continuous trading. Although the market converges to strong-form efficiency, the insider's profits do not converge to zero.

International law prescribes that in a cross-border merger where the acquiror buys 100 percent of the target, the target firm becomes a national of the country of the acquiror. Among other effects, the change in nationality implies a change in investor protection, because the law that is applicable to the newly merged firm changes as well. Therefore, cross-border mergers provide a natural experiment to analyze the effects of changes - both improvements and deteriorations - in corporate governance on firm value. We construct measures of the change in investor protection induced by cross-border mergers in a sample of 506 acquisitions from 39 countries, spanning the period 1989 to 2002. We find that the announcement effect of a cross-border merger for the target firm is higher - relative to a matching, domestic acquisition - the better the shareholder protection and the accounting standards in the country of origin of the acquiror. This result is only significant in acquisitions where the acquiror buys 100 percent of the target, and therefore where the nationality of the target firm changes. In addition, this result is only significant when the acquiror comes from a more-protective country, which suggests that target firms avoid addopting weaker protection via private contracting. Interestingly, we do not find a symmetric effect on the acquiror's return. All in all, we present evidence that the transfer of better corporate governance practices through cross-border mergers is positively valued by markets with weaker corporate governance.

The prevailing view in finance is that the evidence for long-horizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perfectly correlated across horizons under the null hypothesis of no predictability. For example, for the persistence levels of dividend yields, the analytical correlation is 99% between the 1-and 2-year horizon estimators and 94% between the 1-and 5-year horizons, due to the combined effects of overlapping returns and the persistence of the predictive variable. Common sampling error across equations leads to ordinary least squares coefficient estimates and R2s that are roughly proportional to the horizon under the null hypothesis. This is the precise pattern found in the data. The asymptotic theory is corroborated, and the analysis extended by extensive simulation evidence. We perform joint tests across horizons for a variety of explanatory variables, and provide an alternative view of the existing evidence.

Despite extensive disclosure requirements, mutual fund investors do not observe all actions of fund managers. We estimate the impact of unobserved actions on fund returns using the return gap—the difference between the reported fund return and the return on a portfolio that invests in the previously disclosed fund holdings. We document that unobserved actions of some funds persistently create value, while such actions of other funds destroy value. Our main result shows that the return gap predicts fund performance. (JEL G11, G23) Despite extensive disclosure requirements, mutual fund investors do not observe all actions of fund managers. For example, fund investors do not observe the exact timing of trades and the corresponding transaction costs. On the one hand, fund investors may benefit from unobserved interim trades by skilled fund managers who use their informational advantage to time the purchases and the sales of individual stocks optimally. On the other hand, they may bear hidden costs, such as trading costs, agency costs, and negative investor externalities. In this paper, we analyze the

This article develops and estimates a dynamic arbitrage-free model of the current forward curve as the sum of (i) an unconditional component, (ii) a maturity-specific component and (iii) a date-specific component. The model combines features of the Preferred Habitat model, the Expectations Hypothesis (ET) and affine yield curve models; it permits a class of low-parameter, multiple state variable dynamic models for the forward curve. We show how to construct alternative parametric examples of the three components from a sum of exponential functions, verify that the resulting forward curves satisfy the Heath-Jarrow-Morton (HJM) conditions, and derive the risk-neutral dynamics for the purpose of pricing interest rate derivatives. We select a model from alternative affine examples that are fitted to the Fama-Bliss Treasury data over an initial training period and use it to generate out-of-sample forecasts for forward rates and yields. For forecast horizons of 6 months or longer, the forecasts of this model significantly outperform those from common benchmark models.

When the market is incomplete, a new non-redundant derivative security cannot be priced by no-arbitrage arguments alone. Moreover, there will be a multiplicity of stochastic discount factors and each of them may give a different price for the new derivative security. This paper develops an approach to the selection of a stochastic discount factor for pricing a new derivative security. The approach is based on the idea that the price of a derivative security should not vary too much when the payoff of the primitive security is slightly perturbed, i.e., the price of the derivative should be robust to model misspecification. The paper develops two metrics of robustness. The first is based on robustness in expectation. The second is based on robustness in probability and draws on tools from the theory of large deviations. We show that in a stochastic volatility model, the two metrics yield analytically tractable bounds for the derivative price, as the underlying stochastic volatility model is perturbed. The bounds can be readily used for numerical examination of the sensitivity of the price of the derivative to model misspecification.

A reduction in in ation can fuel run-ups in housing prices if people suer from money illusion. For example, investors who decide whether to rent or buy a house by simply comparing monthly rent and mortgage payments do not take into account the fact that in ation lowers future real mortgage costs. We decompose the price-rent ratio into a rational component -meant to capture the "proxy eect" and risk premia -and an implied mispricing. We nd that in ation and nominal interest rates explain a large share of the time-series variation of the mispricing, and that the tilt eect is very unlikely to rationalize this nding.

Nonlinear drift models of the short rate are estimated using data on the short end of the term structure, where the cross-sectional relation is obtained by an analytical approximation. The findings reveal that (i) nonlinear physical drift is not implied unless it is strongly affected by cross-sectional dimensions of the data; (ii) nonlinear risk-neutral drift that allows for fast mean reversion for high rates is desirable to explain and predict observed patterns of yield spreads; and (iii) for higher frequency data from which transitory shocks are removed, (ii) still remains valid although the nonlinearity is somewhat reduced. The Author 2007. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: [email protected], Oxford University Press.

Investors' learning of the state of future real fundamentals from current inflation leads to macroeconomic state dependence of asset valuations and solvency ratios of firms within given rating categories. Since credit spreads are convex functions of solvency ratios, average spreads are higher than spreads at average solvency ratios. Macroeconomic shocks carry risk premiums so that expected default losses are more sensitive to changes in the price of risk than are credit spreads. By incorporating state dependence and increasing the price of risk, the econometrician obtains high credit spreads while maintaining average default losses at historical levels—the credit spreads puzzle. The Author 2007. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: [email protected]., Oxford University Press.