Guidance For Analysts Research Articles

EEGManyPipelines: A Large-scale, Grassroots Multi-analyst Study of Electroencephalography Analysis Practices in the Wild.

The ongoing reproducibility crisis in psychology and cognitive neuroscience has sparked increasing calls to re-evaluate and reshape scientific culture and practices. Heeding those calls, we have recently launched the EEGManyPipelines project as a means to assess the robustness of EEG research in naturalistic conditions and experiment with an alternative model of conducting scientific research. One hundred sixty-eight analyst teams, encompassing 396 individual researchers from 37 countries, independently analyzed the same unpublished, representative EEG data set to test the same set of predefined hypotheses and then provided their analysis pipelines and reported outcomes. Here, we lay out how large-scale scientific projects can be set up in a grassroots, community-driven manner without a central organizing laboratory. We explain our recruitment strategy, our guidance for analysts, the eventual outputs of this project, and how it might have a lasting impact on the field.

The dramaturgy of earnings guidance: an institutional analysis of a soft landing

PurposeMuch in accounting research depends upon equity valuation. Too often, what the stock of publicly traded companies trade at is taken at its face value. Knowing that valuation is a function of performance relative to consensus security analyst expectations, more needs to be known about how these expectations are created and changed. The paper aims to assert that the guidance provided by top-level company management is important to the work product of analysts. The paper develops information from managers involved in these interactions.Design/methodology/approachSemi-structured interviews were conducted with 31 high-level executives employed by large USA companies in several industries. What those companies provided was interpreted through the theoretical lens of institutional theory and amounts to a qualitative content analysis approach to the subject.FindingsThe authors find that institutional theory well describes the important features of analyst guidance. Participants are aware of the broad societal interest that exists in the outcome of the guidance process. The participants accept the need for independent analyst opinions about their companies and their future prospects. In many ways, executives provide analysts more than just raw information and employ strategic structuring for analysts to produce expectations that will allow their companies a favorable pathway to future success as such is judged by the markets. The result is understood as being in the best interests of all market participants, even if it disproportionately benefits current corporate leadership.Research limitations/implicationsResults are dependent upon the interview process, needing the correct questions to be asked and the willingness of interviewees to speak their lived truth. The paper calls into question traditional capital markets studies that evaluate quantitative relationships between projected accounting balances and subsequent stock market prices as a literal truth or as the result of scientific calculation.Practical implicationsMarket participants should be somewhat more skeptical about companies that are routinely able to meet analyst expectations. To a large extent, such displays do not just happen but instead are manufactured to take place by virtual of a careful dance that is mindful of excesses on several sides.Social implicationsThe antagonistic interests of two important groups in the stock market is actually an unrecognized symbiotic dependency that prioritizes continued permission.Originality/valueThe accounting literature is very dependent on the work product of analysts. This is a rare opportunity to peak behind the curtain of their expertise in a critical fashion. The paper breaks ranks with the literature by trying to understand the thinking behind the narratives of capital market participants.

Toward Near‐Field Tsunami Forecasting Along the Cascadia Subduction Zone Using Rapid GNSS Source Models

AbstractOver the past 15 years and through multiple large and devastating earthquakes, tsunami warning systems have grown considerably in their efficacy in providing timely and accurate forecasts to affected communities. However, one part of tsunami warning that still needs improvement is forecasts catered to local, near‐field communities in the time after an earthquake rupture but before coastal inundation. In this study, we test a rapid, Global Navigation Satellite Systems (GNSS)‐driven earthquake characterization model using a large data set of synthetic megathrust ruptures for its near‐field tsunami forecasting potential. We also provide a framework for tsunami forecasting that focuses on the likelihood of exceedance of user‐defined coastal amplitudes that may be of use in the first 15 min following an earthquake. Specifically, we can estimate the earthquake magnitude, without saturation, for 82% of tested ruptures. We can also identify test ruptures as dominantly thrust events, without analyst guidance for 92% of tested thrust ruptures. Finally, modeling the tsunami component of our rapidly estimated fault rupture leads to greater than 80% accuracy in identifying tsunami impact at key coastal amplitude thresholds. This is promising for near‐field warning when the time prior to inundation is limited to tens of minutes. We focus this study on large megathrust ruptures along the quiescent Cascadia subduction zone where there is already a dense GNSS network.

Determination of epoxide impurity in sarpogrelate hydrochloride intermediate by UHPLC and column-switching liquid chromatography

The determination of genotoxic impurities, which is closely related to toxicological concern and daily dose, plays a key role in drug quality control. Epoxide impurity is a kind of genotoxic impurity with an epoxy ring structure during the synthesis process of sarpogrelate hydrochloride. According to the sarpogrelate hydrochloride daily dose, epoxide impurity is limited to the under 5 ppm level. The liquid chromatographic-tandem mass spectrometric (LC/MS/MS) or the gas chromatography-mass spectrometric (GC/MS) method is commonly used to characterize the epoxide impurity of sarpogrelate hydrochloride intermediates. However, these methods are not simple or economical enough to detect epoxide impurity. In this study, we resolved the problem by using the most common UV method with two ideas: one was to improve the absolute sensitivity, and the other was to reduce matrix effects. Both ultra high-performance liquid chromatography (UHPLC with high sensitivity LightPipe™ flow cells) and column-switching liquid chromatography methods were developed and validated for the quantitative determination of epoxide impurity in sarpogrelate hydrochloride intermediates. The limits of detection (LODs) of the UHPLC and column-switching liquid chromatography methods were 0.09 ppm (0.09 μg/g) and 0.33 ppm (0.33 μg/g), and the recovery rates of both methods were 87.2%–132.1% and 97.4%–100.1%, respectively. Both methods established and provided guidance for analysts to develop procedures for impurity control, especially for structures of impurity with similar matrices.

Evaluating Multi-Dimensional Visualizations for Understanding Fuzzy Clusters.

Fuzzy clustering assigns a probability of membership for a datum to a cluster, which veritably reflects real-world clustering scenarios but significantly increases the complexity of understanding fuzzy clusters. Many studies have demonstrated that visualization techniques for multi-dimensional data are beneficial to understand fuzzy clusters. However, no empirical evidence exists on the effectiveness and efficiency of these visualization techniques in solving analytical tasks featured by fuzzy clusters. In this paper, we conduct a controlled experiment to evaluate the ability of fuzzy clusters analysis to use four multi-dimensional visualization techniques, namely, parallel coordinate plot, scatterplot matrix, principal component analysis, and Radviz. First, we define the analytical tasks and their representative questions specific to fuzzy clusters analysis. Then, we design objective questionnaires to compare the accuracy, time, and satisfaction in using the four techniques to solve the questions. We also design subjective questionnaires to collect the experience of the volunteers with the four techniques in terms of ease of use, informativeness, and helpfulness. With a complete experiment process and a detailed result analysis, we test against four hypotheses that are formulated on the basis of our experience, and provide instructive guidance for analysts in selecting appropriate and efficient visualization techniques to analyze fuzzy clusters.

TPFlow: Progressive Partition and Multidimensional Pattern Extraction for Large-Scale Spatio-Temporal Data Analysis.

Consider a multi-dimensional spatio-temporal (ST) dataset where each entry is a numerical measure defined by the corresponding temporal, spatial and other domain-specific dimensions. A typical approach to explore such data utilizes interactive visualizations with multiple coordinated views. Each view displays the aggregated measures along one or two dimensions. By brushing on the views, analysts can obtain detailed information. However, this approach often cannot provide sufficient guidance for analysts to identify patterns hidden within subsets of data. Without a priori hypotheses, analysts need to manually select and iterate through different slices to search for patterns, which can be a tedious and lengthy process. In this work, we model multidimensional ST data as tensors and propose a novel piecewise rank-one tensor decomposition algorithm which supports automatically slicing the data into homogeneous partitions and extracting the latent patterns in each partition for comparison and visual summarization. The algorithm optimizes a quantitative measure about how faithfully the extracted patterns visually represent the original data. Based on the algorithm we further propose a visual analytics framework that supports a top-down, progressive partitioning workflow for level-of-detail multidimensional ST data exploration. We demonstrate the general applicability and effectiveness of our technique on three datasets from different application domains: regional sales trend analysis, customer traffic analysis in department stores, and taxi trip analysis with origin-destination (OD) data. We further interview domain experts to verify the usability of the prototype.

IDSI Methods Working Group Report: Evidence

In the first phase of iDSI (2014-2016), Methods Working Groups were established to investigate three areas of economic evaluation for which additional methods guidance for analysts and policymakers in low- and middle-income countries was deemed particularly valuable. These linked directly to specific Principles for the practice of economic evaluation detailed in the iDSI Reference Case. This iDSI Methods Working Group report details the findings from the investigation to develop an analytical framework which can be used to assess the quality and relevance of any evidence – clinical and cost evidence, that are used in economic evaluations within a health technology assessment (HTA) in LMICs. This is linked to Principle 3: “An economic evaluation should consider all available evidence relevant to the decision problem”. The authors conclude that the majority of the existing tools have been designed to assess quality – i.e. internal validity of the studies, and whilst high-quality economic evaluations require top-quality and unbiased evidence, the relevance – external validity of the included evidence is also highly important. They propose a framework which takes a less prescriptive and more decision-centred approach to evidence assessment.

Orientação estratégica como fonte de desempenho acadêmico: a análise de uma IFES

A busca pela eficácia nas tomadas de decisões estimula cientistas da área de estratégia no desenvolvimento de pesquisas em diferentes segmentos empresariais. Neste contexto, as Instituições Federais de Ensino Superior, em especial as coordenações de curso, emergem como fonte de inquietação e motivação para pesquisas por conta da necessidade de tomadas de decisões ágeis, ao mesmo tempo em que as gestões são atreladas a um processo burocrático e, por vezes, moroso. O objetivo da presente pesquisa é verificar a associação entre a orientação estratégica dos coordenadores de curso com o desempenho acadêmico dos cursos em uma instituição federal de ensino superior. O método utilizado na pesquisa foi a pesquisa quantitativa, via survey, onde os dados foram coletados junto a 46 coordenadores de curso, sendo analisados via estatísticas de Shapiro-Wilk e Kruskal-Wallis. Através dos resultados foi possível perceber que a orientação analista predomina em termos de desempenho (ENADE, DOCENTE, EGRESSO). Por outro prisma verificou-se que o comportamento defensor destaque-se em função do desempenho do conceito de curso. Com relação ao projeto pedagógico de curso não foi possível identificar qual o comportamento é predominante em termos de desempenho. Desta maneira, a orientação analista, recebe maior destaque no desempenho acadêmico.

Bioaccessibility performance data for fifty-seven elements in guidance material BGS 102

BGS 102, a guidance material for bioaccessible arsenic (As) and lead (Pb), was produced during validation of the in vitro Unified Bioaccessibility Method (UBM). This paper reports a compilation of reproducible bioaccessible guidance values for fifty-five additional elements in BGS 102, providing guidance for analysts to broaden the scope of UBM analyses for a wider range of elements based on data collected over an average of 60 separate analytical batches per element. Data are presented in categories for both gastric (STOM) and gastrointestinal (STOM+INT) extraction phases, where reproducibility, measured as relative standard deviation (RSD) was; ≤10% RSD for 27 elements (Mg, Al, Si, P, Ca, Cr, Mn, Co, Ni, As, Rb, Sr, Y, Ba, La, Ce, Pr, Nd, Sm, Eu, Tb, Gd, Dy, Ho, Er, Tm, Yb); between 10 and 20% RSD for 10 elements (Li, K, V, Fe, Cu, Zn, Cd, Lu, Pb, U); and ≥20% RSD for 19 elements in the gastric phase (Be, B, S, Ti, Ga, Se, Zr, Nb, Mo, Ag, Sn, Sb, Cs, Hf, Ta, W, Tl, Bi, Th). Two elements (Mg, Rb) met the ≤10% RSD criteria in the UBM gastrointestinal extraction phase due to the alkaline conditions of this phase precipitating out the majority of determinands. Certain elements, including Na, K, Zn and Se, were found to be a significant component of the extraction fluids with proportionally higher concentrations compared to the guidance material. Bioaccessible fractions (%BAF) were also calculated, but were found to be a less reproducible format for confirming the accuracy of measurements. The low concentration of some elements of interest in BGS 102, such as antimony (Sb), justifies the preparation of an alternative certified reference material (CRM). This paper presents an opportunity to broaden the scope of the UBM method to address food security issues (e.g. Fe and Zn micronutrient deficiencies) and contributions to dietary intake from extraneous dust or soil through evidence of the analytical possibilities and current limitations requiring further investigation.

Earnings Forecast Optimism For U.S. Vs. Non-U.S. Firms

This study examines whether financial analysts are more optimistic in their earnings forecasts for non-U.S. firms than they are for U.S. firms. Several areas of research motivate this examination. First, research shows that global economic influences, such as economic downturns and the desire to increase the international content of portfolios, encourage investors to seek out international investment opportunities in new markets. Second, literature also reveals that emerging markets provide superior growth potential; however, analyzing such firms could introduce task complexity which research finds to be associated with lower forecast accuracy. Finally, research shows that financial analysts cover firms of which they have a favorable opinion. Therefore, because of this literature, it is reasonable to expect that analysts make more optimistic forecasts (over-estimate errors) of the earnings potential of the non-U.S. firms that they choose to follow vs. U.S. firms. Using a summary level measurement of forecast optimism, the authors find that analysts forecasts are more optimistic for non-U.S. firms over both short and long-term horizons. In analyst-level tests, it was found that individual analysts produce more optimistic forecasts for non-U.S. firms in relation to their peers in the long-term; however, that optimism is reduced under short horizons. As portfolios become more internationally diversified, the result of this study will be useful to investors seeking analyst guidance about international investment opportunities.

Inside the black box: modelling health care financing reform in data-poor contexts

Modelling the likely financial resource requirements and potential sources of revenue for health system reform options is of great potential value to policy-makers. Models provide an indication of the financial feasibility and sustainability of such reforms and highlight the implications of alternative reform paths. There has been increasing use of financial models of health sector reform in recent years, particularly since the development of user-friendly software such as SimIns, which was developed by the World Health Organization (WHO) and Deutsche Gesellschaft für Technische Zusammenarbeit (GTZ). This paper outlines the process of developing country-specific spreadsheet-based models to explore the financial resource requirements of health system reform options in South Africa and Tanzania. Building one's own model, although time consuming, allows for greater flexibility and forces the analysts to give careful consideration to the assumptions underlying the model. The core variables in our models are: population, health service utilization rates and unit costs. The paper outlines the types of disaggregation of these variables, the range of possible data sources, key challenges with securing accurate data for each variable, and relevant evidence on which to base key assumptions, and how we went about addressing these challenges. We also briefly review how to model the revenue-generating potential of alternative sources of health care financing. The intention of the paper is to provide guidance for analysts who wish to develop their own models, and to illustrate, with reference to the South African and Tanzanian modelling experience, how one has to adapt to data constraints and context-specific modelling requirements.

Hotel Occupancy: Is the Three-Year Stabilization Assumption Justified?

Corporate and private hotel developers, appraisers, and consultants must make an assumption regarding the period of time it will take a new hotel to reach a stabilized occupancy level. Historically, most developers of future hotel occupancy estimates have assumed a three-year build-up period, although empirical research has not tested this assumption. This research project tests that assumption by analyzing the actual occupancy rates of 3,699 hotels that opened during the previous economic cycle. In addition, this project evaluates the stabilization period based on hotel type, location, size, and service level. This exploratory study develops guidance for analysts of hotel occupancies by evaluating the absolute level of stabilized occupancy by hotel type in an effort to assist with refining the accuracy of prospective financial analyses for new hotels. While this project finds support for the use of a three-year occupancy build-up, it concludes that certain hotel types and locations stabilize more slowly or more quickly, whereas hotel size and service level are not significant determinants of stabilization period. Also, this project finds that certain hotel types stabilize at significantly higher occupancy rates than others.

COOPER-framework: A unified process for non-parametric projects

Practitioners assess performance of entities in increasingly large and complicated datasets. If non-parametric models, such as Data Envelopment Analysis, were ever considered as simple push-button technologies, this is impossible when many variables are available or when data have to be compiled from several sources. This paper introduces by the ‘COOPER-framework’ a comprehensive model for carrying out non-parametric projects. The framework consists of six interrelated phases: Concepts and objectives, On structuring data, Operational models, Performance comparison model, Evaluation, and Result and deployment. Each of the phases describes some necessary steps a researcher should examine for a well defined and repeatable analysis. The COOPER-framework provides for the novice analyst guidance, structure and advice for a sound non-parametric analysis. The more experienced analyst benefits from a check list such that important issues are not forgotten. In addition, by the use of a standardized framework non-parametric assessments will be more reliable, more repeatable, more manageable, faster and less costly.

Table of Contents

Abstract Features Volatility Increasing Investment in Natural Gas Storage, but Also Risk Lee Van Atta Upstream Natural Gas—Prices Natural Gas Price Volatility Veljko Fotak, Scott C. Linn, and Zhen Zhu Upstream Natural Gas—Prices Still a Relationship Between Crude Oil and Natural Gas Prices? Bill Trapmann Upstream Natural Gas—Cross‐Border Most Recent Yearly Figures Show Canada Exported Less, Mexico Imported More Damien Gaul Upstream Natural Gas—Finance Does Analyst Guidance Show Anticipated Winning Sectors in Exploration Services? Robert E. Willett Upstream Natural Gas—LNG Liquidity and Price Competition in the Atlantic LNG Trade Chris Goncalves and Jessica Thompson Columns Federal Regulation and Energy Issues Maybe the Fuel of Choice—Again James J. Hoecker Energy and the Environment Kansas Secretary Unilaterally Bans Coal Plants Jonathan A. Lesser

Executive Compensation and Analyst Guidance: The Link Between CEO Compensation and Expectations Management

During the last decade, a surprisingly high percentage of U.S. companies has fulfilled or beaten analysts' earnings per share forecasts. One of the most frequently cited reasons for this growing tendency is a change in the nature of U.S. executive compensation structure. As stock options have become an increasingly important part of executive compensation, the preservation or enhancement of short term stock value around the earnings announcement has become a priority for managers. Besides earnings management, a widespread way to meet analyst expectations is to inject pessimism into their forecasts by providing analysts with negative clues, or so-called downward guidance. This paper is the first to investigate the relationship between the practice of analyst guidance and executive compensation packages. We document a strong link between expectations management and the relevant options component of CEO compensation, bonus plans, and the percentage of the company's shares owned by the CEO who manages it. In a second set of tests, we show that firms which meet or beat analyst forecasts at the earnings announcement generate positive abnormal returns, which are significantly lower for firms suspected of managing expectations.

Executive Compensation and Analyst Guidance: The Link Between CEO Compensation and Expectations Management

Executive Compensation and Analyst Guidance: The Link Between CEO Compensation and Expectations Management

Adapting Your Simulation for HLA

This article provides guidance for analysts and software developers on how to adapt their exist ing simulations to support the High-Level Architecture (HLA). The first section of the article discusses how to plan for HLA by pro viding strategies that can be used in developing an object model for an existing simulation. The second section discusses modular software de sign techniques for adapting a simulation for HLA with the goal of maximizing interoper ability.