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Abstract:
This study seeks to determine the relation between stock returns and analyst forecast properties, specifically, the dispersion and error of annual earnings forecasts. The results of portfolio sorts, Fama-MacBeth cross-sectional regression models, and Fama and French (1993) factor models indicate firms with low dispersion or error outperform firms with high dispersion or error. Robustness tests show the results are not explained by liquidity, momentum, industry, post-earnings announcement drift, or traditional risk measures. An investment strategy based on forecast properties is shown to produce zero-cost returns of 13% per year, yielding positive returns in all 19 years using an error measure. The results are not attributable to several potential theories. Risk-related theories are eliminated as firms with low dispersion or error ("transparent") outperform firms with high dispersion or error ("opaque"). This remains true even after controlling for volatility measures. Behavioral theories based on optimism are also eliminated as optimistic forecasts only explain a small part of the results. Finally, the results are not related to contrarian-value strategies as the transparent firms outperform in both up and down markets.

Analysts, Analyst forecasts, Earnings forecasts, Stock returns, Information asymmetry, Return factors, Asset pricing models

Abstract:
This study examines the validity of using analyst forecast properties to proxy for information quality. The results suggest that dispersion and error measures are strongly related to financial distress and business risk. Firms with losses, earnings declines, and volatile earnings have a strong tendency towards high dispersion and error. Furthermore, forecast biases are predictable. Firms with low dispersion or error measures have relatively little forecast optimism, while firms with high dispersion or error measures have high amounts of forecast optimism. This finding is driven by loss firms, which tend to have greater dispersion and error. Caution should thus be employed when using dispersion and error measures to proxy for the quality of the information environment.

Analysts, information quality, information asymmetry, forecasts

Abstract:
This paper examines international differences in analyst forecast properties using 42 countries. Properties of the forecasts, specifically dispersion and error, are hypothesized to be a function of country-specific, firm-specific, and discretionary components, the latter component including analyst bias and management manipulation of their firm's information environment. The results suggest that country-specific (e.g., corporate governance structures) and firm-specific (e.g., size) components help determine dispersion and error. The most important component, however, appears to be the discretionary component, as analyzed by profitability. Firms with losses are associated with significantly higher dispersion and error and overwhelming percentages of forecast optimism.

Analyst forecasts, transparency, corporate governance

Abstract:
Street earnings are compared to GAAP earnings for over 29,000 annual observations and 100,000 quarterly observations from 1990 to 2000. Analysis is performed after separating firms by profitability and earnings volatility. Although there is little difference between the two types of earnings for firms with GAAP profits, firms with GAAP losses report significantly higher Street earnings. Firms with annual GAAP losses are also about 20 times more likely to report annual Street profits than firms with annual GAAP profits are likely to report annual Street losses. Additionally, firms with volatile GAAP earnings tend to report higher, smoother Street earnings. The results suggest that some managers attempt to make financial performance look healthier.

analysts, GAAP, Street, earnings, profits, losses

Abstract:
This study examines managerial ethics with regard to earnings reporting and insider trading. Managers of firms with optimistic forecasts or firms with higher Street earnings versus GAAP earnings are considered candidates to be misleading investors. Two hypotheses are examined: 1) that these managers are indeed misleading investors and taking advantage of their deception by selling shares of their firms' stock at inflated prices (the managerial opportunism hypothesis) and 2) that these managers are not misleading investors, but merely believe the optimism surrounding their firms (the managerial optimism hypothesis). The tests find that managers who are candidates for misleading investors to opportunistically sell shares are actually behaving ethically. They buy relatively more shares than other managers, providing support for the managerial optimism hypothesis.

analysts, forecasts, ethics, managerial opportunism

Abstract:
Forecast dispersion, error, and optimism are computed using 36,448 annual observations and 120,022 quarterly observations from 1990 to 2001. Forecast dispersion, error, and optimism all decrease steadily over the sample period, with loss firms showing an especially striking decrease. By the end of the sample period, dispersion and error differences between profit and loss firms are relatively minor, optimism for loss firms is around an unbiased 50%, and pessimism dominates profit firms. The improvement does not appear fully attributable to earnings management, earnings guidance, or Street versus GAAP earnings differences. Furthermore, it appears that loss firm earnings are considerably more difficult to forecast. Given this greater difficulty, analysts actually provide more value when forecasting loss firm earnings.

analysts, forecasts, earnings, dispersion, error, optimism

Abstract:
This study directly compares the performance of tech industry stocks to regulated industry stocks from 1963 to 2002. The stock return performance of the regulated industry is similar to, and in many ways superior to, the performance of the technology industry. For example, $1 invested in 1963 grows to $127 if invested in tech stocks over the 40-year sample period and $117 if invested in regulated stocks, both easily outperforming T-bills, the equally-weighted CRSP index, and the S&P 500. Despite the similar return performance, the regulated industry contains substantially lower risk, as measured by beta and return volatility, versus the technology industry. In addition, the impressive performance of tech stocks is dependent upon two years of particularly high returns (1967 and 1999). The results have interesting implications for traditional notions of risk and for attitudes toward investing in regulated industry stocks.

tech stocks, utilities, bank stocks, market efficiency, long-term stock returns, market efficiency