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This paper aims to focus on the role of financial analysts in corporate fraud in the Chinese stock market.

Data on the analyst coverage and all the types of corporate fraud were obtained for 16,284 company-year observations of Chinese companies. The sample was subsequently divided into those of state-owned enterprises, before and after financial crisis.

The overall results indicate that analyst coverage effectively deters the occurrence of fraud. The sub-sample results suggest that the impact of analysts on deterring fraud is more pronounced in non-state-owned enterprises, especially after the financial crisis. The path analyses show that analyst coverage can deter corporate frauds by affecting information transparency and investor attention. Furthermore, the results show that the deterrence role of financial analysts varies with fraud types: it is more pronounced in deterring disclosure fraud, but not as effective in illegal guarantees and illegal insider dealing. Moreover, analyst coverage can deter the occurrence of fictitious reporting, intentional postponement and material omission.

This paper not only examined the overall fraud probability but also taking into consideration the heterogeneity of the information availability and research focus of financial analysts and examined the analysts’ impact on the occurrence of difference types of fraud. Moreover, this paper explored why financial analysts can deter corporate frauds through path analyses.

Recent evidence suggests that financial analysts have substantial conflicts of interest when publishing their research reports. We argue that not only investors but also listed companies benefit from analyst coverage and suggest that the financial burden of such coverage be shifted entirely to those companies. This article presents a detailed evaluation of a not‐widely‐known proposal that stock exchanges ensure analyst coverage for the companies they list through a levy on their listing fees. We discuss key aspects of the regulatory framework required to ensure the independence of these financial analysts as well as some of its shortcomings. We conclude that this proposal has the potential to ensure the independence of financial analysts more efficiently than the current regulatory approach does.

A principal participant in developing computer‐based information systems is the systems analyst. A wide range of skills and knowledge requirements seems to be necessary to be a systems analyst. To date, few studies have attempted to identify the specific skills that analysts indicate are critical to their success during the systems development life‐cycle process. Identifies and investigates the characteristics of a successful systems analyst’s domain and knowledge base. Specifically, groups domain knowledge into four major categories: technical skills, systems skills, managerial skills, and business skills. From within each category, analysts indicated which skills they perceived to be of importance to perform their job functions as systems analysts successfully. The results help identify the educational and training requirements for future systems analysts that need to be in place for both academic and corporate instructional programmes.

Briefly reviews previous research on the value of investment advisors’ recommendations and presents a study comparing portfolio returns from analysts’ recommendations in the Wall Street Journal’s “Dartboard” contest 1990‐1996, four randomly selected shares and the Dow Jones Industrial Average. Finds the analysts’ portfolio has the highest average returns and standard deviation; and that although some individual analysts have excellent scores in the contest, this is inversely related to the number of times they participate. Suggests that they do not significantly outperform other portfolios, but that contest winners’ tips have significant effects on the market, especially for non‐listed shares. Assesses the implications of the results for the efficient market hypothesis and the share prices of firms with higher asymmetric information.

Drawing on human capital theory and the human capital resources framework, this study explores the knowledge, skills, abilities and other characteristics (KSAOs) required by the emerging role of human resource (HR) analysts. This study aims to systematically identify the key KSAOs and develop a competency model for HR Analysts amid the growing digitalization of work.

Adopting best practices for competency modeling set out by Campion et al. (2011), this study first analyzes 110 HR analyst job advertisements collected from five countries: Australia, Canada, Ireland, the United Kingdom and the USA. Second a thematic analysis of 12 in-depth semistructured interviews with HR analytics professionals from Canada and Ireland is then conducted to develop a novel competency model for HR Analysts.

This study adds to the developing and fast-growing field of HR analytics literature by offering evidence supporting a set of six distinct competencies required by HR Analysts including: consulting, technical knowledge, data fluency and data analysis, HR and business acumen, research and discovery and storytelling and communication.

The research findings have several practical implications, specifically in recruitment and selection, HR development and HR system alignment.

This study contributes to the evolving HR analytics literature in two ways. First, the study links the role of HR Analysts to human capital theory and the human capital resource framework. Second, it offers a timely and empirically driven competency model for the emerging role of HR Analysts.

This paper introduces a new instructional design for executive programs that combined a flipped classroom methodology and experiential learning to address the challenge of teaching highly technical material in a compressed time frame. In practice, when decision-making executives lack technical expertise and face a highly technical problem, they contract for subject-matter expertise (SME) within the firm or through hiring consultants. The authors show how this can be done in a classroom setting to enhance the learning experience.

The classroom approach utilizes students from other programs as analysts for executive MBA (EMBA) teams faced with case analysis that involves technical issues in finance. The analysts act as subject-matter experts for the EMBA students.

Executive student learning is not eroded by relying on the analysts, and, moreover, the use of analysts enhances EMBA student understanding

Executives are able, in a short time frame, to produce high quality analysis by utilizing the subject-matter experts. Executives also learn how to ask the right questions and evaluate the quality of the analysis created by the subject-matter experts. The subject-matter experts, who are also students, derive added benefits of an employment experience in finance, learning how to interpret instructions about the analysis and how to respond to feedback.

The paper illustrates a new course design where the course's technical analysis aspects mimic work environments enhancing student learning.

Prior studies have documented the phenomenon of rounding of analysts' earnings per share (EPS) forecasts in the USA. From the outset, it is unclear if analysts following Singapore firms also similarly engage in the rounding of their EPS forecasts. This study aims to investigate the extent to which analysts engage in rounding of EPS forecasts of firms listed on the Singapore Exchange.

The author conducted his analysis on a sample of analyst EPS forecasts of companies listed on the Singapore Stock Exchange, downloaded from the International Brokers Estimate System (I/B/E/S). This sample consists of 24,219 annual EPS forecasts announced from June 2011 to September 2019. These forecasts were made for 285 unique firms by 48 unique analysts.

The author finds that there is substantial rounding of EPS forecasts, with 9.59% of EPS forecasts examined ending in five- or ten-cent intervals. In supplementary analysis, the author further finds that the level of rounding was comparable across two periods under examination, from 2011 to 2015 and from 2016 to 2019. The author also finds that there was substantial rounding even for forecasts of relatively large magnitudes (i.e. US$1.00 and above).

This study is the first to examine the rounding of analysts' EPS forecasts of Singapore firms. It extends the literature on analyst EPS forecasts and highlights how the phenomenon of rounding of analyst EPS forecasts of US firms extends to Singapore.

Thomson financial database reports a monthly consensus measure of analysts’ forecasts in the third week of every month, and firms’ earnings announcement dates are usually different from the last consensus calculation date. Thus, there is a gap between the last consensus calculation date and the earnings announcement date of firms. This study aims to address the question: “Do analysts issue forecasts that are slightly higher than the consensus number to increase the accuracy of their forecasts?”

This study is based on a sample of 91,172 quarterly earnings forecasts of various firms from 1990 to 2007 made between the last consensus calculation date and quarterly earnings announcement date. Descriptive statistics and statistical tests were used to analyze the data.

The findings propose that contrary to expectation, analysts’ forecasts between the last consensus calculation date and earnings announcement date are smaller than the consensus number. Also, the forecasts made between the last consensus and earnings announcement date is not as informative as forecasts made at other times as they could merely reflect the analysts’ herding behavior resulting from their career concerns.

This study provides a link between the literature that studies firms’ meet or beat analysts’ earnings phenomenon and analysts’ forecast decision-making context. This study also provides useful implications for the literature on the information content of analysts’ forecasts.

This paper aims to investigate how sell-side analysts form expectations on, analyse, and communicate the effects of corporate acquisitions.

The paper reports on case studies of three listed firms who are frequent acquirers. The case data comprise semi-structured interviews and content analysis of analyst reports and corporate reports.

The paper reports three sets of findings. First, the analysts viewed acquisitions as heterogeneous events and, therefore, also treated acquisitions differently depending on factors such as size and acquisition strategy and the perceived “authenticity” of the acquisition (i.e. whether parts of the acquisition would be more accurately described as organic growth and regular capital expenditure (CAPEX) investments). Second, the authors find that analysts struggle with analysing the effects of acquisitions at the announcement date because of a mismatch between the analysts’ need of and the analysts’ access to relevant information. Although clients demand evaluations of announced acquisitions, relevant accounting information is not published until much later and the information at hand only allows for cursory analyses. Finally, the authors find that the analysts’ valuation models were too inflexible to fully incorporate the effects of the acquisition. In sum, the analysts, therefore, developed acquisition-driven investment cases without supporting accounting information and without converting expected acquisitions into forecasts.

By adopting a qualitative case study research design, the paper contributes to the ongoing efforts to open the “black-box” of sell-side analyst behaviour. In particular, the unique research design focusses on effects related to specific corporate events (acquisitions) rather than analysts’ everyday work.

Using data from securities analysts, who are awarded status by the third-party organization Institutional Investor magazine, we examine the emergence of competition and articulate a model of competitive response among actors aware of the importance of status and some of the dimensions on which it may be gained. We predict analysts’ initiating or ceasing coverage of stocks in response to other analysts initiating coverage on stocks they cover. We find that competition can emerge because of status seeking rather than as a response to own capabilities or market needs, with compelling, and potentially negative, market implications for overt status seeking.