This paper examines the market reaction to a press release issued by Intel on Thursday, September 21, 2000. In response to that release, Intel’s stock price dropped 30 percent, erasing over $120 billion of shareholder wealth. By analyzing the press release in conjunction with analyst reports and by using a discounted cash flow valuation model, it is argued that the information conveyed by the announcement was not sufficient to explain the stock price drop. In an effort to explain this controversial conclusion, the paper documents the puzzling and procyclical role of analysts’ recommendations regarding Intel. Surprisingly, analysts were more strongly recommending purchase of the stock in August at $75 than they were recommending purchase in September at $40. This suggests a positive feedback between stock price movements and analyst recommendations that may increase the volatility of prices.

Because much of the value of equity depends on the option characteristics of investment projects, it is not feasible to calculate equity duration directly. As a result, recent literature has focused on estimating equity duration empirically. By using 25 size and book-to-market portfolios, this paper shows that estimates of equity duration are critically dependent on the specifications of the regression model used to estimate equity duration. In particular, including all three Fama-French factors in the regression can have a dramatic impact on the estimate coefficients.

This paper attempts to shed light on the continuing debate regarding executive compensation by comparing the income of S&P 500 CEOs with that of the Presidents of elite private universities. The results reveal that university presidents are paid only a fraction of what CEOs are paid – less than 5% in 2000. Nonetheless, universities are able to attract leaders with qualifications and accomplishments equivalent to that of the most distinguished CEOs. Furthermore, university presidents appear to be willing to work as hard and as much in the interests of their constituents as corporate CEOs despite the lack of any meaningful incentive clauses in their contracts. These results suggest that the standard principal agent model used in evaluating compensation needs to be extended significantly before it can be applied to situations in a few select people are recruited for highly paid and visible jobs that offer the chance to lead major institutions.

This paper attempts to shed light on the asset pricing questions reaised by recent empirical research. Fama and French, among others, find that variables that are supposed to explain cross-sectional returns, specifically risk parameters that emerge from asset pricing models, have little explanatory power. On the other hand, firm characteristics such as size and book-to-market ratios, that do not fall out of any asset pricing model, are quite successful in explaining the cross-sectional distribution of historical returns. This has led to the suspicion that Fama-French type results are due to data problems, such as selection bias or data mining. In this paper, a new, direct estimate of expected returns is constructed using the discounted cash flow model and the IBES data. Consistent with previous empirical work, these new estimates of expected returns are found largely to be uncorrelated theoretical risk parameters, but to be significantly correlated with firm size and book-to-market ratios. However, the correlation between DCF expected returns and book-to-market ratios is found to be negative, as opposed to the positive correlation between book-to-market ratios and historical returns.