Narrow Results

The main purposes of this introduction chapter are (i) to give an overview of the following 109 papers, which discuss investment analysis, portfolio management, and financial derivatives; (ii) to classify these 109 chapters into nine topics; and (iii) to classify the keywords in terms of chapter numbers.

Consensus earnings forecasts matter to investment practitioners in forming profitable investment portfolios and matter to researchers in studying how earnings inform the market. This study revisits the issue of considering analyst heterogeneity in forming better analyst consensus earnings forecasts (Clement, 1999; Clement and Tse, 2003; Brown and Mohd, 2003). Based on quarterly data for US firms from 1994 to 2017, the study finds that characteristics-based consensus forecasts outperform the simple mean consensus to predict abnormal returns in both the three-day window around and the two-month drift window after earnings announcements. They perform as well as the median consensus does to predict abnormal returns in the three-day window around earnings announcements but outperform the median consensus in the drift window. Investors may find these findings relevant to their investment decisions, and researchers may find them relevant to the studies of earnings informativeness.

In this chapter, we extend the usage of CAPM to the problem of estimating the cost of capital in funding risky projects. This estimation involves the estimation of betas, which we had shown in the last chapter, as well as the estimation of market risk premium. The latter is a bit more tricky and sometimes requires auxiliary regressions involving constraining the intercept to be zero. The latter is the same as regression through the origin. Although constrained regression is more general and can apply to the constraint of any sets of coefficients in a linear regression equation, we consider only the case of regression through the origin here.