Financial Analysts' Forecasts and Stock Recommendations reviews research related to the role of financial analysts in the allocation of resources in capital markets. The authors provide an organized look at the literature, with particular attention to important questions that remain open for further research. They focus research related to analysts' decision processes and the usefulness of their forecasts and stock recommendations. Some of the major surveys were published in the early 1990's and since then no less than 250 papers related to financial analysts have appeared in the nine major research journals that we used to launch our review of the literature. The research has evolved from descriptions of the statistical properties of analysts' forecasts to investigations of the incentives and decision processes that give rise to those properties. However, in spite of this broader focus, much of analysts' decision processes and the market's mechanism of drawing a useful consensus from the combination of individual analysts' decisions remain hidden in a black box. What do we know about the relevant valuation metrics and the mechanism by which analysts and investors translate forecasts into present equity values? What do we know about the heuristics relied upon by analysts and the market and the appropriateness of their use? Financial Analysts' Forecasts and Stock Recommendations examines these and other questions and concludes by highlighting area for future research.

This paper reviews research regarding the role of financial analysts in capital markets. The paper builds on the perspectives provided by Schipper (1991) and Brown (1993). We categorize papers published mainly since 1992 and selectively discuss aspects of these papers that address or suggest key research topics of ongoing interest in seven broad areas: analysts' decision processes, the determinants of analyst expertise and distributions of individual analysts' forecasts, the informativeness of analysts' research outputs, analyst and market efficiency with respect to information, effects of analysts' economic incentives on their research outputs, effects of the institutional and regulatory environment (including cross-country comparisons), and the limitations of databases and various research paradigms.

In this study we test whether financial analysts' use their earnings forecasts to make stock recommendations. We hypothesize that if analysts use earnings forecasts as a basis for stock recommendations, the likelihood of a buy (sell) recommendation ought to increase (decrease) when the analyst's earnings forecast becomes more optimistic (pessimistic) relative to the market's expectation. The data supports this hypothesis. We also test the extent to which analysts' stock recommendations are based on public and/or on private earnings information. Private information is measured as the difference between the analysts own earnings forecast and the consensus forecasts of other analysts. Public information is measured as the difference between the consensus forecast and the random walk forecast. Our data show that stock recommendations are related to both private and public earnings information, private information is more important. We also find that the relationship between recommendations and forecasts is stronger where earnings are more value relevant. Factors such as higher earnings persistence and growth opportunities, lower market risk and larger firm size make stock recommendations more responsive to earnings forecasts. Stock recommendations are related to forecasted earnings surprises even when the forecast revision is held constant.

Financial analysts provide information in their research reports and thereby help forming expectations of a firm’s future business performance. Thus, it is essential to recognize analysts who provide the most precise forecasts and the accounting literature identifies characteristics that help finding the most accurate analysts. Tanja Klettke detects new relationships and identifies two new determinants of earnings forecast accuracy. These new determinants are an analyst’s “general forecast effort” and the “number of supplementary forecasts”. Within two comprehensive empirical investigations she proves these measures’ power to explain accuracy differences. Tanja Klettke’s research helps investors and researchers to identify more accurate earnings forecasts.

This thesis focuses on the three primitive value drivers of each company valuation model that is based on fundamental analysis: the discount rate, the expected future payoffs during the explicit forecasting period, and the terminal value at the end of the explicit forecasting period. While the first factor is analyzed theoretically by incorporating the government into the classical valuation framework, this thesis studies the other two factors by investigating forecasts made by professional investors, i.e. financial analysts. In the first part we show that the government's and the shareholders discount rate usually differ and analyze how the government's and shareholders different objectives lead to conflicts in the context of capital budgeting. The empirical part of this thesis shows that macroeconomic information is frequently used by financial analysts when updating their earnings expecations and that target price forecastsmade by financial analysts can be used to predict abnormal returns.

Financial analysts play an ambivalent role on financial markets: On the one hand investors and the media frequently follow their advice, on the other hand they are regularly discredited when their forecasts or recommendations prove to be erroneous. This cumulative thesis explores the informational content of financial analysts’ forecasts for investors by addressing three specific topics: Consensus size as a rudimentary investment signal, the association of analysts’ target prices with business sentiment, and the consistency of analysts’ different investment signals in the context of the 2008 financial crisis. Overall, the thesis provides additional evidence that investors can profit from analysts’ forecasts and recommendations. However, it is also shown that investors need to be very selective about which signal to rely on and in which context to use these because analysts’ investment signals can also be heavily biased and erroneous. About the author: Jan-Philipp Matthewes studied ‘Economics’ at the University of Cologne, Germany, and holds a Dean’s Award from the Faculty of Economics and Social Sciences. His research focus on financial analysts evolved while working in equity research at a leading German bank. The PhD-thesis was supervised by Prof. Dr. Martin Wallmeier, Finance and Accounting, at the University of Fribourg, Switzerland. Since 2013 Jan-Philipp Matthewes is the managing director of the boutique private equity firm ‘Matthewes Capital Invest GmbH’.