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.

​Earnings forecasts are ubiquitous in today’s financial markets. They are essential indicators of future firm performance and a starting point for firm valuation. Extremely inaccurate and overoptimistic forecasts during the most recent financial crisis have raised serious doubts regarding the reliability of such forecasts. This thesis therefore investigates new determinants of forecast errors and accuracy. In addition, new determinants of forecast revisions are examined. More specifically, the thesis answers the following questions: 1) How do analyst incentives lead to forecast errors? 2) How do changes in analyst incentives lead to forecast revisions?, and 3) What factors drive differences in forecast accuracy?

This study conducts a comprehensive review of the literature published during 1996- 2017 to identify the factors that affect the accuracy of financial analysts' forecasts. We organize our review around three main groups, namely, (a) drivers of analyst forecast accuracy, (b) quality financial reporting, and (c) accounting standards. Among the several factors found, some factors (experience of the analyst, earnings quality, audit quality, IFRS adoption, and annual report readability) have a positive relationship with the accuracy of analysts' forecasts while others (politically connected firms, firms audited by Non-Big 4, and international GAAP differences) have a negative relationship. Our findings contribute to future research by examining the factors affecting analyst forecast accuracy from different perspectives, which will prove to be useful for academicians, regulators, investors, and financial analysts.

The importance of information in the formation process of security prices has a long history. The dissemination of information can take on different forms depending on the legal constraints. However, in all developed financial markets, financial analysts play a prominent role in collecting, analysing and diffusing information. Financial analysts typically supply future earnings estimates and stock picking advices in the form of recommendations. Earnings estimates are the essential part of security valuation by analysts and investors. They have even become an integral part of financial reporting in the financial press. Early research has accumulated evidence that these estimates are optimistically biased. More recently, empirical studies have found that analysts' optimistic bias is lessening, that its extent differs across analysts, firm characteristics and countries. Broadly speaking, this dissertation investigates the determinants of financial analyst forecasts bias. In the first essay, I examine the relative accuracy of European financial analysts' earnings forecasts and its determinants. I show that the results obtained for US analysts can not be generalised to European analysts who face a seemingly different job market as well as several different institutional and economic environments. In the second essay, I investigate the influence of financial analysts' location on their performance. More precisely, I examine the relative performance of local versus foreign analysts on Latin American stock markets. I find foreign analysts to be more timely and more accurate than their local counterparts. In addition, I document stronger price reactions after foreign analysts' forecast revisions than after those of local analysts. The third essay is related to the declining pattern of financial analyst forecast bias. In particular, I investigate whether US CEOs compensation arrangements give CEOs incentives to manipulate analysts' expectations downward in order to release ea.

Prior to Regulation Fair Disclosure (Reg FD) some management spent considerable time and effort guiding analyst earnings estimates, often through detailed reviews of analysts' earnings models. In this paper I use proprietary survey data from the National Investor Relations Institute to identify firms that reviewed analysts' earnings models prior to Reg FD and those that did not. Under the maintained assumption that firms conducting reviews implicitly or explicitly guided analysts' earnings forecasts, I document firm characteristics associated with the decision to provide private managerial earnings guidance. Then, I document the characteristics of 'guided' versus 'unguided' analyst earnings forecasts. Findings demonstrate an association between several firm characteristics and guidance practices: managers are more likely to review analyst earnings models when the firm's stock is highly followed by analysts and largely held by institutions, when the firm's market-to-book ratio is high, and its earnings are important to valuation (high Industry-ERC R2), but hard to predict because its business is complex (high # of Segments). A comparison of guided and unguided quarterly forecasts indicates that guided analyst estimates are more accurate, but also more frequently pessimistic. An examination of analysts' annual earnings forecasts over the fiscal year does not distinguish between guidance and no guidance firms; both experience a quot;walk downquot; in annual estimates. To distinguishing between guidance and no guidance firms, one must examine quarterly earnings news: unguided analysts walk down their annual estimates when the majority of the quarterly earnings news is negative, guided analysts walk down their annual estimates even though the majority of the quarterly earnings news is positive.