What is the Chance that the Equity Premium Varies over Time? Evidence from Regressions on the Dividend-Price Ratio

We examine the evidence on excess stock return predictability in a Bayesian setting in which the investor faces uncertainty about both the existence and strength of predictability. When we apply our methods to the dividend-price ratio, we find that even investors who are quite skeptical about the existence of predictability sharply modify their views in favor of predictability when confronted by the historical time series of returns and predictor variables. Correctly taking into account the stochastic properties of the regressor has a dramatic impact on inference, particularly over the 2000-2005 period.

Predictable Returns and Asset Allocation: Should a Skeptical Investor Time the Market?

We investigate optimal portfolio choice for an investor who is skeptical about the degree to which excess returns are predictable. Skepticism is modeled as an informative prior over the R2 of the predictive regression. We find that the evidence is sufficient to convince even an investor with a highly skeptical prior to vary his portfolio on the basis of the dividend-price ratio and the yield spread. The resulting weights are less volatile and deliver superior out-of-sample performance as compared to the weights implied by an entirely model-based or data-based view

What is the Chance That the Equity Premium Varies Over Time? Evidence From Regressions on the Dividend-Price Ratio

We examine the evidence on excess stock return predictability in a Bayesian setting in which the investor faces uncertainty about both the existence and strength of predictability. When we apply our methods to the dividend-price ratio, we find that even investors who are quite skeptical about the existence of predictability sharply modify their views in favor of predictability when confronted by the historical time series of returns and predictor variables. Correctly taking into account the stochastic properties of the regressor has a dramatic impact on inference, particularly over the 2000–2005 period

Essays on financial economics

My dissertation focuses on two areas of financial economics. First, I look at the purchase and sale of operating units by companies. The first chapter characterizes the behavior of value-maximizing firms, which may invest in new capital, purchase existing assets or sell assets. This approach yields an endogenous selection model that links asset purchases and sales to fundamental properties of the firm. Empirical tests confirm the predictions of the model. In particular, return on assets and size strongly predict when firms purchase or sell assets, and the size of the transaction covaries with the marginal value of capital. The second chapter explores cross-sectional variation in abnormal returns associated with asset purchases and sales. Ceteris paribus, a dollar increase in the transaction size leads to a 11¢ gain to buyers and a 14¢ gain to sellers. This demonstrates that asset sales improve the allocative efficiency of capital. However, this is tempered by agency problems. The market discounts asset purchases by firms with poor governance measures, and acquisitions by large firms lead to lower returns. Further, while a dollar increase in transaction size creates 21¢ of value to strong governance firms, the corresponding value for weak governance firms equals only 3¢. The third chapter explores return predictability from the perspective of a skeptical investor. Previous literature has tended toward two polar viewpoints: predictability is useful only if the statistical evidence is incontrovertible, or that predictability should affect portfolio choices even if the evidence is weak. This paper models an intermediate view. We investigate optimal portfolio choice for an investor who is skeptical about the amount of predictability in the data. Skepticism is modeled as an informative prior over the improvement in the Sharpe ratio generated by using the predictor variable. The resulting weights are less volatile, and, as we show, deliver superior out-of-sample performance compared with weights implied by diffuse priors, dogmatic priors, and regression analysis

The expected real return to equity

The expected return to equity--typically measured as a historical average--is a key variable in the decision making of investors. A recent literature based on analysts forecasts and practitioner surveys finds estimates of expected returns that are sometimes much lower than historical averages. This study presents a novel method that estimates the expected return to equity using only observable data. The method builds on a present value relationship that links dividends, earnings, and investment to market values via expected returns. Given a model that captures this relationship, one can infer the expected return. Using this method, the estimated expected real return to equity ranges from 4 to 5.5 percent. Furthermore, the analysis indicates that expected returns have declined by about 2 percentage points over the past forty years. These results indicate that future returns to equity may be lower than past realized returns.Stock - Prices ; Forecasting ; Investments ; Securities

Research and development, profits and firm value: a structural estimation

Is the return to private R&D as high as believed? This study identifies a flaw in the production function approach to estimating the return to R&D. I provide new estimates based on a structural estimation approach that incorporates uncertainty about the outcome from R&D. The results shed light on the rate of innovation, the impact of an innovation on profits, and the market value of the R&D stock. The parameter estimates imply a mean return to R&D of 3.7-5.5%, much lower than previous values. The analysis also demonstrates the unsuitability of using the return to R&D as a basis for policy decisions on tax subsidies to R&D.Research and development ; Rate of return