scholarly journals Causal language intensity in performance commentary and financial analyst behaviour

2018 ◽  
Vol 46 (1-2) ◽  
pp. 3-31 ◽  
Author(s):  
Shuyu Zhang ◽  
Walter Aerts ◽  
Huifeng Pan
Keyword(s):  
Financial Analyst ◽  
Language Intensity ◽  
Causal Language

Explain or conceal? Causal language intensity in annual report and stock price crash risk

2021 ◽  
Vol 94 ◽  
pp. 715-725
Author(s):  
Dongmin Kong ◽  
Lu Shi ◽  
Fan Zhang
Keyword(s):  
Stock Price ◽  
Annual Report ◽  
Crash Risk ◽  
Language Intensity ◽  
Causal Language

A Challenge to the Young Financial Analyst: The Investment Manager of the Future

1960 ◽  
Vol 16 (2) ◽  
pp. 23-24
Author(s):  
Edmund A. Mennis
Keyword(s):  
Financial Analyst ◽  
The Future ◽  
Investment Manager

scholarly journals Consistency of causal claims in observational studies: a review of papers published in a general medical journal

BMJ Open ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. e043339
Author(s):  
Camila Olarte Parra ◽  
Lorenzo Bertizzolo ◽  
Sara Schroter ◽  
Agnès Dechartres ◽  
Els Goetghebeur
Keyword(s):  
Medical Journal ◽  
Observational Studies ◽  
The Other ◽  
Research Papers ◽  
General Medical Journal ◽  
Outcome Relationship ◽  
Causal Statement ◽  
Data Source ◽  
Published Research ◽  
Causal Language

ObjectiveTo evaluate the consistency of causal statements in observational studies published in The BMJ.DesignReview of observational studies published in a general medical journal.Data sourceCohort and other longitudinal studies describing an exposure-outcome relationship published in The BMJ in 2018. We also had access to the submitted papers and reviewer reports.Main outcome measuresProportion of published research papers with ‘inconsistent’ use of causal language. Papers where language was consistently causal or non-causal were classified as ‘consistently causal’ or ‘consistently not causal’, respectively. For the ‘inconsistent’ papers, we then compared the published and submitted version.ResultsOf 151 published research papers, 60 described eligible studies. Of these 60, we classified the causal language used as ‘consistently causal’ (48%), ‘inconsistent’ (20%) and ‘consistently not causal’(32%). Eleven out of 12 (92%) of the ‘inconsistent’ papers were already inconsistent on submission. The inconsistencies found in both submitted and published versions were mainly due to mismatches between objectives and conclusions. One section might be carefully phrased in terms of association while the other presented causal language. When identifying only an association, some authors jumped to recommending acting on the findings as if motivated by the evidence presented.ConclusionFurther guidance is necessary for authors on what constitutes a causal statement and how to justify or discuss assumptions involved. Based on screening these papers, we provide a list of expressions beyond the obvious ‘cause’ word which may inspire a useful more comprehensive compendium on causal language.

Corporate‐Level Influences On Internal Capital Allocation: The Role Of Financial Analyst Performance Projections

2021 ◽  
Author(s):  
John R. Busenbark ◽  
Matthew Semadeni ◽  
Mathias Arrfelt ◽  
Michael C. Withers
Keyword(s):  
Capital Allocation ◽  
Financial Analyst ◽  
Internal Capital ◽  
Corporate Level

Netflix, Inc.: The Customer Strikes Back

2012 ◽  
pp. 1-7
Author(s):  
Daniel Shively ◽  
Rajkumar Venkatesan
Keyword(s):  
Customer Lifetime Value ◽  
Financial Analyst ◽  
Customer Lifetime ◽  
Lifetime Value

This case is an updated version of “Netflix Inc.: DVD Wars” (UVA-M-0763), and was written as a replacement for it.A financial analyst is asked to appraise the value of Netflix’s stock at a time of unprecedented turmoil for the company. This case introduces customer lifetime value (CLV) as a useful metric for subscription-based businesses.

Financial Analyst Coverage, Method of Payment and Wealth Effects in M&As

2013 ◽  
Author(s):  
Mathieu Luypaert ◽  
Tom Van Caneghem
Keyword(s):  
Wealth Effects ◽  
Financial Analyst ◽  
Analyst Coverage ◽  
Method Of Payment

scholarly journals Systematic survey of the causal language use in systematic reviews of observational studies: a study protocol

BMJ Open ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. e038571
Author(s):  
Mi Ah Han ◽  
Gordon Guyatt
Keyword(s):  
Systematic Reviews ◽  
Observational Studies ◽  
Language Use ◽  
Causal Effect ◽  
Data Extraction ◽  
Open Science ◽  
Third Party ◽  
Systematic Survey ◽  
Assessment Development ◽  
Causal Language

IntroductionSometimes, observational studies may provide important evidence that allow inferences of causality between exposure and outcome (although on most occasions only low certainty evidence). Authors, frequently and perhaps usually at the behest of the journals to which they are submitting, avoid using causal language when addressing evidence from observational studies. This is true even when the issue of interest is the causal effect of an intervention or exposure. Clarity of thinking and appropriateness of inferences may be enhanced through the use of language that reflects the issue under consideration. The objectives of this study are to systematically evaluate the extent and nature of causal language use in systematic reviews of observational studies and to relate that to the actual intent of the investigation.Methods and analysisWe will conduct a systematic survey of systematic reviews of observational studies addressing modifiable exposures and their possible impact on patient-important outcomes. We will randomly select 200 reviews published in 2019, stratified in a 1:1 ratio by use and non-use of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Teams of two reviewers will independently assess study eligibility and extract data using a standardised data extraction forms, with resolution of disagreement by discussion and, if necessary, by third party adjudication. Through examining the inferences, they make in their papers’ discussion, we will evaluate whether the authors’ intent was to address causation or association. We will summarise the use of causal language in the study title, abstract, study question and results using descriptive statistics. Finally, we will assess whether the language used is consistent with the intention of the authors. We will determine whether results in reviews that did or did not use GRADE differ.Ethics and disseminationEthics approval for this study is not required. We will disseminate the results through publication in a peer-reviewed journals.RegistrationOpen Science Framework (osf.io/vh8yx).

scholarly journals Analyst Coverage And Audit Efforts: Empirical Approach To Audit Hours

2015 ◽  
Vol 31 (3) ◽  
pp. 795 ◽  
Author(s):  
Hong Min Chun ◽  
Chang Seop Rhee
Keyword(s):  
Measurement Error ◽  
Global Financial Crisis ◽  
Positive Relation ◽  
Financial Analyst ◽  
Analyst Following ◽  
Analyst Coverage ◽  
Audit Failure ◽  
Audit Market ◽  
Audit Fee ◽  
Unique Dataset

This study investigates the effect of financial analyst coverage on audit efforts by examining the association between the number of analyst followings and audit hours. Existing literatures report that there are inconsistent results between analyst coverage and audit efforts, and most studies used audit fee as a proxy for audit efforts. However, audit fee may cause measurement error. We consider that audit hour is a better proxy for measuring audit efforts than audit fee because practically auditors are less likely to charge extra audit fee for their additional efforts in competitive audit market. Also, after audit engagement contract, the amount of audit fee is almost fixed. Thus, it cannot reflect variable auditors decision whether inputting additional efforts or not during audit service. Intuitively, audit hours are more accurate measure of audit efforts as long as it indicates how much hours auditors work. For the above reasons, we use unique dataset of audit hours in Korea. We find that analyst coverage is positively associated with audit hour. This means auditors make more efforts on their audit service in case of greater analyst following, and they crucially consider reputational damage from audit failure when they provide audit services to their clients with great analyst following. Next, we still observe positive relation in both pre and post global financial crisis periods. Lastly, we find that BIG4 auditors are more concerned about reputational loss than Non-Big4 in case of greater analyst following.

Firm Credit Ratings and Financial Analyst Forecast Performance

2018 ◽  
Vol 20 (3) ◽  
Author(s):  
Nathan H. Jeppson ◽  
Matthew C. Geiszler ◽  
David F. Salerno
Keyword(s):  
Credit Ratings ◽  
Analyst Forecast ◽  
Financial Analyst ◽  
Forecast Performance
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