We examine the optimal trading strategy for a CRRA investor who maximizes the expected utility of wealth on a finite date and faces transaction costs. Closed-form solutions are obtained when this date is uncertain. We then show a sequence of analytical solutions converge to the solution to the problem with a deterministic finite horizon. Consistent with the common life-cycle investment advice, the optimal trading strategy is found to be horizon dependent and largely buy and hold. Moreover, it might be optimal for the investor in our model not to buy any stock, even when the risk premium is positive. Further analysis of the optimal policy is also provided.

From 1981 to 1991 the mean earnings of immigrants fell further behind those of natives in Hong Kong, with the earnings gap widening from 11.3% to 25.5%. Earnings divergence of this magnitude is rather unusual among countries that receive many immigrants. We show that earnings divergence in Hong Kong is mainly due to divergence between skill prices for immigrants' education and for natives' education. Intertemporal shift in the demand for skills caused by economic restructuring in Hong Kong has a differential impact not only on prices of different levels of skill, but also on prices of skills from different sources.

We examine the optimal trading strategy for a CRRA investor who maximizes the expected utility of wealth on a finite date and faces transaction costs. Closed-form solutions are obtained when this date is uncertain. We then show a sequence of analytical solutions converge to the solution to the problem with a deterministic finite horizon. Consistent with the common life-cycle investment advice, the optimal trading strategy is found to be horizon dependent and largely buy and hold. Moreover, it might be optimal for the investor in our model not to buy any stock, even when the risk premium is positive. Further analysis of the optimal policy is also provided.

An interesting question in assessing value relevance of accounting variables is whether measures of value relevance are materially affected by market inefficiencies. We explore this question in two steps: First, we analytically examine the impact of market inefficiencies on the estimation of coefficients in value relevance regressions and derive a procedure that corrects potential biases caused by such inefficiencies. The procedure adjusts contemporaneous stock prices for future risk adjusted price changes, and yields value relevance coefficient estimates that capture both contemporaneous and delayed market reactions. Second, we apply this procedure to three types of studies that have attracted much attention in the accounting literature: 1) the value relevance of earnings and book values; 2) the value relevance of residual income value estimates; and 3) the value relevance of accruals and cash flows. We compare coefficient estimates obtained from conventional value relevance regressions with those from regressions employing our adjustment procedure, and find statistically significant differences in both level and return regression coefficient estimates. The magnitude of differences in coefficient estimates for return regressions is large enough to affect economic inferences. We find that coefficients of lagged price deflated residual income value estimates move significantly closer toward a predicted value of one implying a meaningful reduction of bias. Last, we find that cash flows now have significantly larger coefficient estimates than accruals consistent with their greater persistence.

A substantial literature has developed to estimate the “true” cyclicality of real wages, that is, composition bias free. Two major issues are addressed in this article: aggregation of heterogeneous workers and potential bias in the measurement of the labor input. A general analysis of the biases is presented, and alternative approaches in the literature are nested in a single framework. Estimates based on an efficiency units concept that avoids the usual aggregation problems are presented. Composition bias underestimates the usual parameters of interest unless both the price and the quantity of the labor input are adjusted appropriately.

We examine the valuation performance of a comprehensive list of value drivers and find that multiples derived from forward earnings explain stock prices remarkably well: pricing errors are within 15 percent of stock prices for about half our sample. In terms of relative performance, the following general rankings are observed consistently each year: forward earnings measures are followed by historical earnings measures, cash flow measures and book value of equity are tied for third, and sales performs the worst. Curiously, performance declines when we consider more complex measures of intrinsic value based on short‐cut residual income models. Contrary to the popular view that different industries have different “best” multiples, these overall rankings are observed consistently for almost all industries examined. Since we require analysts’ earnings and growth forecasts and positive values for all measures, our results may not be representative of the many firm‐years excluded from our sample.