Inside the “Black Box” of Sell‐Side Financial Analysts

Inside the 'Black Box' of Sell-Side Financial Analysts

This dissertation is composed of three chapters. The first chapter explores the importance of previously identified factors in explaining the variation in analysts’ earnings forecast error. As earnings forecasts are the main input in determining price targets and consequently stock recommendations, much of the process through which analysts process their input remains in a so-called “black box”. This study attempts to shed light on these inputs. First, it reveals that forecast errors are stable over time, and analysts do not efficiently integrate past information in their forecasts. Second, analysts do not factor in expectations related to the macroeconomic conditions for the underlying forecast horizon. Analysts overreact (underreact) to positive (negative) macroeconomic expectations on both GDP and consumer sentiment index. Third, this study decomposes analysts’ forecast errors variance by observable characteristics and fixed effects. Importantly, the analysis shows that there is an unobserved, time-invariant component related to the firm-analyst dimension that explains much of the variance in the forecast errors. This component is not yet captured by the existing observable characteristics which, at date, have a trifling effect on their own in explaining the variation in analysts’ forecast error. <br>In the second chapter, I investigate the role of financial reporting frequency in analysts’ earnings forecasts. I addresses two questions. First, does mandatory quarterly reporting benefit financial analysts in decreasing their earnings forecast error and dispersion? Second, to what extent common accounting standards increase the convergence of analysts’ information set for firms with different reporting frequencies? I find little support to the claim that regulation forcing firms to issue more frequent financial information benefits financial analysts. Compared to a control sample of semiannual reporting firms in the European market, analysts issuing earnings forecasts for firms with mandatory quarterly frequency experience higher forecast error and dispersion. When firms are mandated to report not only on a quarterly frequency, but also under International Financial Reporting Standards (IFRS), analysts’ both forecast error and dispersion decrease. However, while IFRS does benefit analysts by increasing the quality of their information set in absolute terms, they do not wipe out the relative noise associated with mandatory quarterly statements. <br>The third chapter focuses on how financial analysts adapt to the passage of regulations aiming at limiting conflicts of interest in the investment banking industry. This last chapter investigates analysts’ price targets and recommendations, and unravels a new form of conflicts of interest. Specifically, it investigates whether affiliated brokers issue unfavourable ratings on their clients’ competitors in the product market (rivals). The findings document an important gap between ratings for affiliated and rival firms. Specifically, brokers issue persistently higher ratings on firms with which they are affiliated compared to their rivals. Importantly, the Sarbanes-Oxley Act and the related financial regulations aiming at curbing the conflicts of interests had no significant impact in reducing this gap. As such, affiliated brokers continue to indirectly favour their clients. This form of conflict was devoid of adequate attention in prior research. Furthermore, investors are unaware of the existence of such conflict in the short-run.

Financial analysts’ earnings forecasts are more consistent with stock recommendations when their earnings forecasts are more accurate (Loh and Mian 2006, Ertimur et al. 2007). This suggests that analysts use other information in their private valuation models in addition to earnings forecasts especially when earnings have greater uncertainty. Recent studies show that political connections are important for firm valuation and are associated with future positive returns and future positive operating performance (Faccio 2006, Cooper et al. 2010). In this study, I examine how a firm’s political connections affect stock recommendation informativeness as well as the efficiency with which analysts translate their earnings forecasts into stock recommendations. Using data from the Federal Election Commission through the Center for Responsive Politics from 1993 – 2011, I first show that analysts’ recommendations are less informative when firms have political connections. This relation holds for both All-Star and non-All-Star analysts, upgrade and downgrade recommendations, as well as initiation and non-initiation recommendations. Second. I show that analysts’ earnings forecast accuracy is less consistent with recommendation informativeness when firms are politically connected. This inconsistency appears to be driven by non-All-Star analysts, upgrade recommendations, and non-initiation recommendations. The findings of this study imply that political connection information is one source of important nonfinancial disclosure that influences how analysts map their earnings forecasts into stock recommendations.

PurposeThe purpose of this paper is to examine whether analysts’ cash flow forecasts improve the profitability of their stock recommendations and whether the positive effect of cash flow forecasts on analysts’ stock recommendation performance varies with firms’ earnings quality.Design/methodology/approachTo test the authors’ predictions, they identify a sample of 161,673 stock recommendations with contemporaneous earnings forecasts and/or cash flow forecasts and regress market-adjusted stock returns on a binary variable that proxies for the issuance of cash flow forecasts while controlling for contemporaneous earnings forecast accuracy, earnings quality, analysts’ forecast experience and capability and certain firm characteristics. The authors’ test results are robust to alternative measures of recommendation profitability, earnings quality and the use of recommendation revisions instead of recommendation levels.FindingsThe authors find that when analysts issue cash flow forecasts concurrently with earnings forecasts, their stock recommendations lead to higher profitability than when they only issue earnings forecasts, after controlling for analysts’ forecast capability. Moreover, the authors document that the contemporaneous positive relationship between cash flow forecasts and recommendations profitability is stronger for firms with low earnings quality than for firms with high earnings quality. The findings suggest that cash flow forecasts issued by analysts in response to market demand likely play a more important role in firm valuation than cash flow forecasts issued by analysts mainly because of supply-side considerations.Research limitations/implicationsFuture research could build on these findings to conduct further investigation on the alternative incentives for analysts’ forecasts of sales growth and long-term growth rates.Practical implicationsThese findings may also help investors to better assess the quality of analysts’ research outputs and to identify superior stock recommendations.Originality/valueThis study provides insight into the role of cash flow forecasts in firm valuation and adds fresh evidence to the debate on the usefulness of cash flow forecasts. It extends the stream of research on the characteristics of analyst forecasts and increases our knowledge about the role of analysts in the financial market.

This paper investigates how corporate governance quality affects the analyst’s stock recommendations, forecast efficiency and target price accuracy on New York Stock Exchange. In particular, as corporate governance is often uncertain and ambiguous to investors, expert financial advisors may use transparent corporate governance information to set their recommendations and improve the level of accuracy of their earnings forecasts. According to agency and signaling theories, good governance mechanisms aim to mitigate agency conflicts and boost corporate transparency. Thus, we argue that they can serve as mediators during the forecasting process and we expect a strong significant relationship between the effectiveness of corporate governance mechanisms and analyst activity. Five hypotheses are tested with a large sample of 154 US market firms over a 17-year period (2004–2020). Our empirical findings point out some special features of US stock markets. We find evidence that analysts tend to issue favorable recommendations, more accurate, less dispersed and more optimistic earnings forecasts for most well-governed firms. Furthermore, we show that higher-quality governance transparency is an important determinant of financial analysts’ behavior in the USA. The results also indicate that higher-quality governance appears valuable with financial analysts during pre- and post-crisis period, while it is not generally detected in COVID-19 times. However, we report the weakness of analysts’ outputs–governance quality for small firms. Thus, our findings cast doubts over the corporate governance-based analyst practices of US small and unaffiliated firms. The main implication of these findings is to improve understanding of how investors’ behavioral characteristics affect the transmission mechanism of information in money market and capital market prices. This paper has important implications for the decision making of financial analysts and investors by requesting firms to significantly improve their information environments in the good and bad times. It also offers insights into how firms establishing good corporate governance mechanisms can help the analysts to predict future stock prices.

This paper examines whether valuation estimates based on analysts' earnings forecasts are consistent with their stock recommendations. Because earnings forecasts are linked to value and recommendations reflect analysts' opinions of value relative to current price, earnings forecasts and stock recommendations should be linked in a predictable manner. I consider four possible valuation models of how earnings forecasts and stock recommendations are linked. These models include two specifications of the residual income model, a price-earnings-to-growth (PEG) model, and analysts' projections of long-term earnings growth. The results provide little evidence that analysts' recommendations are explained by either residual income model specification. However, both the PEG model and analysts' projections of long-term earnings growth explain analysts' stock recommendations. The relation between the valuation models and future returns is also examined. Analysts' projections of long-term earnings growth have the greatest explanatory power for stock recommendations, but investment strategies based on these projections have the least association with future excess returns. Overall, the evidence suggests that analysts' recommendations are more correlated with heuristic valuation models than with present value models, and buy-and-hold investors would earn higher returns relying on present value models that incorporate analysts' earnings forecasts than on analysts' recommendations.

This thesis is made of three distinct chapters. The second and third chapters constitute the core of this work. Both focus on financial analysts and their performance depending on whether they are specialized along country or sector lines. The first chapter sets the stage of the analysis. It presents and evaluates the relative strength of country and sector factors in stock returns. Short abstracts of these three chapters appear below. Chapter 1 This paper investigates the relative influences of industrial and country factors in international stock returns. Until very recently, academic research has consistently found that country factors dominate industrial factors. This result is in contradiction with practitioners beliefs. This paper re-examines this issue by analyzing a sample of more than 4000 stocks quoted in 20 developed countries. We find that on average the country effect still dominates stock returns over the period 1997-2000. This result has to be interpreted with caution though, as an analysis that allows for time-varying relative influences demonstrates the rapidly increasing impact of industry effects in recent times. We find, in particular, that this trend is common to all 20 developed countries considered and not only to those that are member of the European Monetary Union. We interpret this result as evidence of the increasing globalization of international equity markets. Chapter 2 Brokerage houses normally structure their research activities along either country or sector lines. I investigate whether organizational structure affects the quality of financial analysts’ earnings forecasts. Specifically, I compare the performance of country-specialized financial analysts with that of sector-specialized financial analysts. The former issue forecasts considerably more accurately than the latter. Country specialists benefit from an informational advantage over sector specialists. A superior knowledge of country-specific factors, as well as geographical proximity between analysts and the firms they cover, are significant determinants of this advantage. Chapter 3 Brokerage houses usually organize their research activities along country or economic sector dimensions. We evaluate which research structure provides most value to investors. To this end, we study the relative information content of stock recommendations issued by country-specialized analysts versus those issued by sector-specialized analysts. Our findings reveal that the former issue more valuable recommendations. The strength of country-specific commonalities explains at least part of the out performance of country-specialized financial analysts. Surprisingly, while analysts’ geographical location has been shown in the literature to be a determinant of earnings forecast accuracy, it is not a source of a comparative advantage when it comes to stock recommendations.

The impact of equity incentive plans on analysts’ earnings forecasts and stock recommendations for Chinese listed firms: An empirical study

Coexistence and Dynamics of Overconfidence and Strategic Incentives

Coexistence and Dynamics of Overconfidence and Strategic Incentives

Coexistence and Dynamics of Overconfidence and Strategic Incentives

The quality of equity research by financial analysts is a prerequisite for an efficient capital market. This study investigates the quality of earnings forecasts and stock recommendations for initial public offerings (IPOs) in Germany. The empirical study includes 12,605 earnings forecasts and 6,209 stock recommendations of individual analysts for the time period from 1997 to 2004. The focus of this study is on analysing the potential conflicts of interest that arise when the analyst is affiliated with the underwriter of an IPO. In a universal banking system these conflicts of interest are usually more pronounced and therefore interesting to investigate. The empirical findings for the German financial market suggest that earnings forecasts and stock recommendations of the analysts belonging to the lead‐underwriter are on average inaccurate and biased, indicating some conflicts of interest. Moreover, the stock recommendations of the analysts that are affiliated with the lead‐underwriter are often too optimistic resulting in a significant long‐run underperformance for the investor. In contrast, unaffiliated analysts provide better earnings forecasts and stock recommendations that result in a superior performance for the investor.

How Do Analysts Use Their Earnings Forecasts in Generating Stock Recommendations?

Analysts' use of earnings forecasts in predicting stock returns: Forecast horizon effects

We examine the relation between analysts' earnings forecasts and their stock recommendations. We hypothesize that if analysts base their recommendations on their earnings forecasts, recommendations will be more (less) favorable relative to consensus recommendations when analysts' earnings forecasts are more optimistic (pessimistic) relative to consensus earnings forecasts. The data support this hypothesis. We find the relation between recommendations and forecasts to be stronger when earnings are more value relevant. Factors such as lower earnings volatility, higher growth, lower market risk, healthier financial conditions, and larger analyst following make stock recommendations more responsive to earnings forecasts. Stock recommendations are also more responsive when the forecast horizon is longer.