Interest To Analysts Research Articles

Environmental Justice Specialization and Corporate ESG Performance: Evidence from China Environmental Protection Court

In order to implement the dual-carbon strategy and achieve sustainable economic development, it is essential to guarantee environmental protection through the establishment of an effective environmental rule of law. This study employs a quasi-natural experiment, namely the establishment of environmental protection courts in China’s intermediate people’s courts, to investigate the impact on the ESG performance of A-share listed companies from 2010 to 2022. A double-difference model is utilized for this purpose. This study reveals that the specialization of environmental justice is an effective means of promoting the ESG performance of enterprises. The results of mechanism tests indicate that the specialization of environmental justice has a positive impact on the ESG performance of enterprises, primarily by enhancing external supervision and garnering greater media attention and analyst interest. Furthermore, heterogeneity analysis reveals that the influence of environmental justice specialization on corporate ESG performance is particularly pronounced in eastern regions, contexts characterized by high environmental uncertainty and heavily polluting enterprises. These findings offer invaluable insights into the development of environmental justice and the advancement of sustainable economic growth.

Information disclosure as a means of minimizing asymmetric financial reporting: The role of market reaction

This study investigates the effect of information disclosure on financial accounting information comparability. We use a sample of Chinese A-share companies listed from 2001 to 2018 and discover that higher information disclosure quality can increase financial accounting information comparability. Our results reveal that high information disclosure ratings attract greater investor and analyst interest than does increased liquidity and that increased financial accounting information comparability is the main transmission pathway for this effect. Furthermore, the results remain robust after instrumental variables are used to solve endogeneity problems and also after robustness tests. Our findings suggest that regulatory activity to improve public firms’ information disclosure in the Chinese stock market can increase the market’s efficiency. In addition, when facing agency problems, enterprises should defer to external supervision and governance from investors.

Selective quantification of diclofenac from groundwater and pharmaceutical samples by magnetic molecularly imprinted polymer-based sorbent coupled with the HPLC-PDA detection.

Diclofenac (DCF) is a pharmaceutical contaminant of water bodies and therefore, improvement of analytical techniques for its removal and quantitation is one of the current interests of analysts. Herein, DCF selective magnetic molecularly imprinted polymer (MMIP) has been fabricated and characterized by Fourier transform-infrared spectroscopy, thermogravimetric analysis, vibrating scanning magnetometer, scanning electron microscopy, high-resolution transmission electron microscope, energy-dispersive X-ray spectroscopy, and Brunauer-Emmett-Teller analyzer. Furthermore, the protocol for the quantification of DCF using MMIP-HPLC-PDA combo has been optimized by investigating the effect of the amount of MMIP, type and volume of eluent, and variation of pH. The optimized protocol suggested a method detection limit of 0.042ng mL-1 and linearity of results in the range 0.1-100ng mL-1 (R2 = 0.99). The fabricated material offered recovery of DCF up to 96.38-99.46% from groundwater and pharmaceutical samples with a relative standard deviation of <4%. In addition, the material was found selective and sensitive for DCF among its analogous drugs like mefenamic acid, ketoprofen, fenofibrate, aspirin, ibuprofen, and naproxen.

Using equilibrium thermodynamics to study thermochemical processes in arc discharges used in atomic emission spectral analysis (review)

Until the beginning of the 21st century, the arc discharge was the main source of excitation of the atomic spectra of elements during routine atomic emission spectral analysis. The wide application of this spectral source at the same time aroused great interest of analysts in the study of complex thermochemical processes occurring at its electrodes and in the discharge plasma. This was due to the need to improve the metrological and informational characteristics of the analysis. Equilibrium thermodynamics has often been used to carry out such studies. It is shown that three levels of the thermodynamic approach can be distinguished here, differing in the complexity of the applied apparatus of thermodynamics and the information content of the results obtained. Numerous examples of the application of these levels of approach to the study of thermochemical processes occurring in the electrode or in the discharge plasma are given. The main advantages and disadvantages of the approaches used, which provide only qualitative information about the ongoing processes, are noted. The main disadvantage is the impossibility of predicting the composition of the arc plasma from the initial composition of the condensed sample. The most informative is the generalized thermodynamic model of thermochemical processes in a DC arc discharge from the sample surface and from the electrode crater. The model is based on the division of a non-stationary non-equilibrium system of an arc discharge into successive quasi-stationary subsystems. They correspond to the stage of sample evaporation and thermochemical transformation of its components in the discharge plasma. According to the model, the total equilibrium composition of the evaporated sample is initially calculated. This determines the initial composition of the arc plasma. Then, the total equilibrium composition of the arc plasma is calculated and the transition to the intensities of the spectral lines of the analytes is performed. The correctness of the generalized model, which gives semi-quantitative results, is confirmed by comparison with experimental data.

Brokerage trading volume and analysts’ earnings forecasts: a conflict of interest?

Using unique new data, we examine whether brokerage trading volume creates a conflict of interest for analysts. We find that earnings forecast optimism is associated with higher brokerage volume, even controlling for forecast and analyst quality, recommendations, and target prices. However, forecast accuracy is also significantly associated with higher volume. When analysts change brokerage houses, they bring trading volume with them, influencing trading volume at the new brokerage. This indicates that analysts drive the volume effects we observe. Consistent with a reward for generating volume, brokerage houses are less likely to demote analysts who generate more volume. Finally, analysts strategically adjust forecast optimism based on expected volume impact. Analysts become more (less) optimistic if their optimistic forecasts in the prior year were more (less) successful at generating volume. However, consistent with higher costs to increasing accuracy, analysts do not update accuracy based on expected volume impact. Overall, our results are consistent with a brokerage trading volume conflict of interest moving analysts towards more optimistic earnings forecasts, despite the volume reward for accuracy.

Automated – Multitasking Methodology to Study Business Indicators using Data Science

The objective is to provide a multitasking methodology to study business indicators automatically using Data Science. This consists of 7 stages: data preparation, univariate analysis, bivariate analysis, grouping patterns, reduction of dimensions, supervised model training and validation. R, R-Studio (processing) and Rmarkdown (visualization) are used. The methodology is applied on four study cases (two from manufacturing sector and two from services) and provide useful information for firms and teaching-learning processes. The methodology distinguishes between media and response indicators, comprises more than 10 analysis methods, includes the three statistical scopes (univariate, bivariate and multivariate) and automatically answers six questions of interest for analysts.

The incremental informativeness of sell-side earnings forecasts. Evidence for the Warsaw Stock Exchange

We investigate whether earnings forecasts issued by sell-side analysts are incrementally informative about the returns of firms listed on the Warsaw Stock Exchange (WSE), a moderately-developed, postcommunist capital market. Our sample covers the fiscal years 2008-2016. The informativeness of earn- ings (and earnings forecasts) is defined as the association between earnings (earnings forecasts) and returns. Our findings indicate that the mean earnings forecasts issued by sell-side analysts are incremen- tally informative about firm returns beyond the earnings reported. This result does not depend on firm size, profitability, or market return. The findings indicate that such forecasts incorporate useful incremen- tal valuation information and that the incremental informativeness of these forecasts serves to protect the interests of analysts’ clients.

Broker Trading Volume: A Conflict of Interest?

Using unique new data, we examine whether brokerage trading volume creates a conflict of interest for analysts’ earnings forecasts. We find that forecast optimism is associated with higher brokerage volume, even controlling for forecast and analyst quality, recommendations, and target prices. When analysts change brokerage firms, they bring this trading volume with them, influencing trading volume at the new brokerage house. This indicates that analysts drive the volume effects we observe. Consistent with a reward for generating volume, brokerage houses are less likely to demote analysts who generate more volume. Finally, analysts strategically adjust forecast optimism based on expected volume impact. Analysts become more (less) optimistic if their optimistic forecasts in the prior year were more (less) successful at generating volume. Overall, our results are consistent with a brokerage trading volume conflict of interest moving analysts towards more optimistic earnings forecasts.

RETRACTED: Discovery of Characteristic Sequential Patterns Based on Two Types of Constraints

This article proposes a method for discovering characteristic sequential patterns from sequential data by using background knowledge. In the case of the tabular structured data, each item is composed of an attribute and an attribute value. This article focuses on two types of constraints describing background knowledge. The first one is time constraints. It can flexibly describe relationships related to the time between items. The second one is item constraints, it can select items included in sequential patterns. These constraints can represent the background knowledge representing the interests of analysts. Therefore, they can easily discover sequential patterns coinciding the interests as characteristic sequential patterns. Lastly, this article verifies the effect of the pattern discovery method based on both the evaluation criteria of sequential patterns and the background knowledge. The method can be applied to the analysis of the healthcare data.

An eye tracking study of bloodstain pattern analysts during pattern classification

Bloodstain pattern analysis (BPA) is the forensic discipline concerned with the classification and interpretation of bloodstains and bloodstain patterns at the crime scene. At present, it is unclear exactly which stain or pattern properties and their associated values are most relevant to analysts when classifying a bloodstain pattern. Eye tracking technology has been widely used to investigate human perception and cognition. Its application to forensics, however, is limited. This is the first study to use eye tracking as a tool for gaining access to the mindset of the bloodstain pattern expert. An eye tracking method was used to follow the gaze of 24 bloodstain pattern analysts during an assigned task of classifying a laboratory-generated test bloodstain pattern. With the aid of an automated image-processing methodology, the properties of selected features of the pattern were quantified leading to the delineation of areas of interest (AOIs). Eye tracking data were collected for each AOI and combined with verbal statements made by analysts after the classification task to determine the critical range of values for relevant diagnostic features. Eye-tracking data indicated that there were four main regions of the pattern that analysts were most interested in. Within each region, individual elements or groups of elements that exhibited features associated with directionality, size, colour and shape appeared to capture the most interest of analysts during the classification task. The study showed that the eye movements of trained bloodstain pattern experts and their verbal descriptions of a pattern were well correlated.

Fiscal Sustainability: Conceptual, Institutional, and Policy Issues

The chronic nature of sovereign debt crises has resulted in the growing interest of analysts in finding both their real causes and the mechanisms of cross-country transmission - the so-called contagion effect. In this paper, we will try to answer the frequently asked question: what is the “safe” level of public debt (i.e. what level helps to avoid the risk of sovereign default)? Simultaneously, we will address various conceptual, institutional, and statistical dilemmas related to the definition and measurement of public debt.

Reliability forecasting for operators’ situation assessment in digital nuclear power plant main control room based on dynamic network model

With the technical development of computer hardware and software, digitalization is a trend in large-scale complex systems such as nuclear power plants (NPPs). It changes the way main control room (MCR) operators interact with systems. Faced with these technical changes, operators need to continue improving their situation assessment (SA) reliability level. In addition to evaluate operators’ SA reliability, managers and shift supervisors also want to forecast their SA reliability level. There have been many studies with respect to operators’ SA, but most of them are static analysis method and cannot be applied to predict operators’ SA reliability. So, on the basis of different forecasting approaches and observation data, how to predict the operators’ SA reliability level has became a problem that many analyst interest in. In this paper, first we identified the influence factors associated with SA reliability, and then we developed the SA reliability model, finally we proposed a reliability forecasting model by integrating time series forecasting method with dynamic network model (DNM). Our experiment verification focused on steam generator tube rupture (SGTR) event, using the forecasting model, we demonstrated how to predict operators’ SA reliability during the course, and the prediction results are consistent with measurement results.

A New Approach For Discovering Top-K Sequential Patterns Based On The Variety Of Items

Abstract This paper proposes a method that discovers various sequential patterns from sequential data. The sequential data is a set of sequences. Each sequence is a row of item sets. Many previous methods discover frequent sequential patterns from the data. However, the patterns tend to be similar to each other because they are composed of limited items. The patterns do not always correspond to the interests of analysts. Therefore, this paper tackles on the issue discovering various sequential patterns. The proposed method decides redundant sequential patterns by evaluating the variety of items and deletes them based on three kinds of delete processes. It can discover various sequential patterns within the upper bound for the number of sequential patterns given by the analysts. This paper applies the method to the synthetic sequential data which is characterized by number of items, their kind, and length of sequence. The effect of the method is verified through numerical experiments.

What happens when a stock is added to the Nasdaq-100 index? What doesn’t happen?

Purpose – Prior research on additions to the S &amp; P 500 and the smaller MidCap 400 and SmallCap 600 indexes reach different conclusions regarding the key variables that explain the cross-section of announcement period abnormal returns. Most notable in this regard is that liquidity measures, long thought to be of importance, do not appear to explain abnormal returns of the S &amp; P 500 when other factors are controlled for. By contrast, they do appear to matter for additions to the smaller stock indexes. To explore this difference, the purpose of this paper is to analyze the abnormal returns upon announcement that a stock will be added to the Nasdaq-100 Index in a cross-sectional manner, controlling for several possible alternative factors. Design/methodology/approach – This paper analyzes abnormal returns upon announcement that a stock will be added to the Nasdaq-100 Index. The authors consider several possible sources of the positive price effects in a multivariate setting that controls simultaneously for measures of liquidity, arbitrage risk, operating performance and investor interest and awareness. The authors then analyze both trading volume and the bid-ask spreads. The authors finally examine analyst and investor interest, focussing on changes in analyst coverage. Findings – The authors find that only liquidity variables are significant, but that factors representing feedback effects on the firm’s operations and level of managerial effort are not. The authors find that the average bid/ask spreads of stocks added to the Nasdaq-100 index are lower after the addition. The authors also find that the number of analysts following a stock increases significantly after addition, verifying increased analyst interest. Both forms of evidence are consistent with the hypothesis that the additions are associated with enhanced liquidity for the stocks. Originality/value – The authors conclude that what does happen to a Nasdaq stock when it is announced that it will be added to the Nasdaq-100 Index is that more analysts are drawn to it, and its market liquidity is enhanced. The authors conclude that what does not happen is that there is no evidence of significant effects of enhanced managerial effort or operating performance associated with the inclusion. This difference is noteworthy because it suggests that a certification effect of additions to the S &amp; P indexes associated with S &amp; P’s selection process are unique to it and do not apply to the Nasdaq-100 Index additions based on market cap alone. The results provide indirect evidence on the existence and significance of the certification effect associated with additions to the S &amp; P indexes.

Analyst Interest as an Early Indicator of Firm Fundamental Changes and Stock Returns

ABSTRACTWe posit that a change in analyst interest in a firm is an early indicator of the firm's future fundamentals, capital market activities, and stock returns. We measure increases in analyst interest by obser.ving analysts who do not cover a firm but participate in that firm's earnings conference call, and we measure decreases in analyst interest by observing analysts who cover a firm, yet are absent from that firm's call. We find that increases in analyst interest are positively associated with future changes in firm fundamentals and capital market activities, while decreases in analyst interest are negatively associated with capital market activities. We also find that increases (decreases) in analyst interest are positively (negatively) correlated with future stock returns over the next three months and that a hedge portfolio yields a significant abnormal return. Overall, our study shows that analyst interest is a novel and early indicator of future firm fundamentals and capital market consequences.JEL Classifications: G11; G12; G14; G31; M41.

Analyst Interest, Market Visibility, and Stock Returns

We posit that a change in analyst interest in a firm is an early indicator of the firm’s future fundamentals, capital market activities, and stock returns. We measure increases in analyst interest by observing analysts who do not cover a firm but participate in that firm’s earnings conference call, and we measure decreases in analyst interest by observing analysts who cover a firm yet are absent from that firm’s call. We find that increases in analyst interest are positively associated with future changes in firm fundamentals and capital market activities, while decreases in analyst interest are negatively associated with capital market activities. We also find that increases (decreases) in analyst interest are positively (negatively) correlated with future stock returns over the next three months and that a hedge portfolio yields a significant abnormal return. Overall, our study shows that analyst interest is a novel and early indicator of future firm fundamentals and capital market consequences.

On the differences between child and adult analysis

The goals and central methodological requirements of psychoanalysis (neutrality, abstinence, a fixed setting, awareness of transference and the related analyst's interest in the inner world of the analysand, the use of one's own psyche as a “working tool”, etc.) do not depend on the analysand's age. In this paper, I study the similarities and differences between child and adult analyses, with particular emphasis on the methodological differences arising from the child-adult level. The perspective opens from the viewpoint of two psychoanalytic treatment paradigms: firstly, the developmental process and secondly, self-observation, and how they are made possible. A theoretical discussion is followed by a comparison between two cases of analysis, one of which began when the analysand was 6-years-old and the other when the analysand was 30-years-old Both analysands had the same key problem: sadomasochistic tendencies in life. In the comparison, the psychoanalytic process is found the same, but differences in the methodological questions emerge from the analysands' different ways of communication and possibilities for self-observation, as well as the more layered and rigid psychic structure adults have compared with children, whose psychic structure is more plastic, though it may have become fixed at a very early stage There are several differences in the external frame of the psychoanalyses.

Summarization and matching of density-based clusters in streaming environments

Density-based cluster mining is known to serve a broad range of applications ranging from stock trade analysis to moving object monitoring. Although methods for efficient extraction of density-based clusters have been studied in the literature, the problem of summarizing and matching of such clusters with arbitrary shapes and complex cluster structures remains unsolved. Therefore, the goal of our work is to extend the state-of-art of density-based cluster mining in streams from cluster extraction only to now also support analysis and management of the extracted clusters. Our work solves three major technical challenges. First, we propose a novel multi-resolution cluster summarization method, called Skeletal Grid Summarization (SGS), which captures the key features of density-based clusters, covering both their external shape and internal cluster structures. Second, in order to summarize the extracted clusters in real-time, we present an integrated computation strategy C-SGS, which piggybacks the generation of cluster summarizations within the online clustering process. Lastly, we design a mechanism to efficiently execute cluster matching queries, which identify similar clusters for given cluster of analyst's interest from clusters extracted earlier in the stream history. Our experimental study using real streaming data shows the clear superiority of our proposed methods in both efficiency and effectiveness for cluster summarization and cluster matching queries to other potential alternatives.

Diversity In Analyst Coverage

This paper examines the effect of intra-industry "earnings informativeness" and proprietary firm information on variation in security analyst coverage within industries. Earnings informativeness is defined as the extent to which privately developed or obtained information about one firms' earnings provides useful information about the earnings of its industry co-members. Proprietary information provides signals concerning future firm profitability, relative to industry competitors, resulting from such factors as new product developments and innovations in production processes. The results reveal that levels of analyst coverage relative to mean levels of industry-specific analyst interest is significantly positively associated with intra-industry earnings informativeness and size-adjusted annual research and development expenditures (a proxy for proprietary firm information). The findings also show that certain determinants of analyst coverage (e.g., firm size and institutional ownership) identified in the prior literature as explaining variation in aggregate analyst following also hold at the industry level. Finally, the paper examines whether the model variables found to possess explanatory power within industries can also serve to explain observed variation in inter-industry levels of analyst interest and the results suggest that they can.

The Effect Of Conference Call Initiations On Analyst Coverage And Institutional Ownership

&lt;p class="08BodyText" style="text-align: justify; line-height: normal; text-indent: 0in; margin: 0in 0.5in 0pt; mso-pagination: none;"&gt;&lt;em style="mso-bidi-font-style: normal;"&gt;&lt;span style="color: black; font-size: 10pt;"&gt;&lt;span style="font-family: Times New Roman;"&gt;The study empirically examines changes in institutional ownership and analyst coverage in the years following conference call initiations. We find significant increases in both variables in the years following initiations of conference calls after controlling for confounding factors. These results complement prior research on the benefits of disclosures and suggest that expanded disclosures create additional institutional and analyst interest in stocks.&lt;/span&gt;&lt;/span&gt;&lt;/em&gt;&lt;/p&gt;&lt;p class="08BodyText" style="text-align: justify; line-height: normal; text-indent: 0in; margin: 0in 0in 0pt; mso-pagination: none;"&gt;&lt;span style="color: black; font-size: 10pt;"&gt;&lt;span style="font-family: Times New Roman;"&gt;&amp;nbsp;&lt;/span&gt;&lt;/span&gt;&lt;/p&gt;