Knowledge that Transforms

Using a multivariate vector-autoregression approach, this paper investigates causal relations and dynamic interactions among asset returns, real activity, and inflation in the postwar United States. Major findings are (1) stock returns appear Granger-causally prior and help explain real activity; (2) with interest rates in the vector autoregression, stock returns explain little variation in inflation, although interest rates explain a substantial fraction of the variation in inflation; and (3) inflation explains little variation in real activity.

The authors characterize the conditions under which efficient portfolios put small weights on individual assets. These conditions bound mean returns with measures of average absolute covariability between assets. The bounds clarify the relationship between linear asset pricing models and well-diversified efficient portfolios. The authors argue that the extreme weightings in sample efficient portfolios are due to the dominance of a single factor in equity returns. This makes it easy to diversify on subsets to reduce residual risk, while weighing the subsets to reduce factor risk simultaneously. The latter involves taking extreme positions. This behavior seems unlikely to be attributable to sampling error.

The authors explore the determinants of liquidation values of assets, particularly focusing on the potential buyers of assets. When a firm in financial distress needs to sell assets, its industry peers are likely to be experiencing problems themselves, leading to asset sales at prices below value in best use. Such illiquidity makes assets cheap in bad times and so ex ante is a significant private cost of leverage. The authors use this focus on asset buyers to explain variation in debt capacity across industries and over the business cycle, as well as the rise in U.S. corporate leverage in the 1980s.

This paper reexamines the integration of the Canadian and U.S. stock markets in the 1977-86 period that is relatively free from capital controls. The study employs both the capital asset pricing model and the arbitrage pricing theory frameworks. Under both models, the evidence is consistent with segmentation in the 1977-81 subperiod, but supports integration in the 1982-86 subperiod. Using the arbitrage pricing theory framework, the author finds that the Canadian stocks interlisted on the U.S. exchanges and NASDAQ are priced.in an integrated market and segmentation is predominant for the noninterlisted Canadian stocks.

This paper first characterizes the predictable components in excess rates of returns on major equity and foreign-exchange markets using lagged excess returns, dividend yields, and forward premiums as instruments. Vector autoregressions demonstrate one-step-ahead predictability and facilitate calculations of implied long-horizon statistics, such as variance ratios. Estimation of latent variable models then subjects the vector autoregressions to constraints derived from dynamic asset pricing theories. Examination of volatility bounds on intertemporal marginal rates of substitution provides summary statistics that quantify the challenge facing dynamic asset pricing models.

The author studies the divestiture decisions of managers who care about their reputations. Managers' divestiture and investment decisions are publicly observable, but managers privately observe signals with respect to the future payoff distribution of investments they have initiated. He establishes that in equilibrium there is too little divestiture. These inefficiencies create the opportunity for wealth-enhancing divestiture-motivated takeovers. A key result is that only managers of targets with "middle of the road" asset specificity should consider the takeover threat credible. These findings suggest that uniqueness of assets is an important determinant of both agency costs and takeover activity. The author's analysis leads to several empirical predictions.

This paper investigates whether managers rely on dividends to obtain a higher price in a stock offering and whether the stock price reaction to dividend and offering announcements justifies such a coordination. The evidence does not support either conjecture. Issuing firms are not more likely to pay or increase dividends than nonissuing firms. Moreover, there is little evidence that firms time stock-offering announcements right after dividend declarations to benefit from the attendant information disclosure. The analysis of dividend and stock-offering announcement effects suggests few if any benefits from linking dividend and stock-offering announcements.

Ordinary Least Squares regression ignores both heteroscedasticity and cross-correlations of abnormal returns; therefore, tests of regression coefficients are weak and biased. A portfolio ordinary least squares (POLS) regression accounts for correlations and ensures unbiasedness of tests, but does not improve their power. The authors propose portfolio weighted least squares (PWLS) and portfolio constant correlation model (PCCM) regressions to improve the power. Both utilize the heteroscedasticity of abnormal returns in estimating the coefficients; PWLS ignores the correlations, while PCCM uses intra- and inter-industry correlations. Simulation results show that both lead to more powerful tests of regression coefficients than POLS.

Restrictions on trading by insider agents are analyzed using an optimal contracting framework. Prohibition of insider trading is shown to be Pareto preferred if, and only if, a revelation or moral hazard problem exists. If prohibition of insider trading is valuable, then trade registration with a delay is shown to be as valuable as a complete prohibition. Short-selling restrictions, however, are generally of less value than complete prohibition. Finally, regulation of insider agent trading by governmental institutions and/or professional associations is discussed.

R. Geske and H. E. Johnson (1984) develop an equation for the American put price and obtain accurate prices using a method requiring quadrivariate normal integrals evaluated over an interval containing four equally spaced exercise points. The authors show that a modification of their method, which uses optimal placement of exercise points, yields, in most cases, accurate values using nothing more than bivariate normals. In the more difficult (deep-in-the-money) cases, trivariate normals suffice.