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Wang, Jingyan, and Nihar B. Shah. "Ranking and Rating Rankings and Ratings." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 09 (April 3, 2020): 13704–7. http://dx.doi.org/10.1609/aaai.v34i09.7126.
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Cardinal scores collected from people are well known to suffer from miscalibrations. A popular approach to address this issue is to assume simplistic models of miscalibration (such as linear biases) to de-bias the scores. This approach, however, often fares poorly because people's miscalibrations are typically far more complex and not well understood. It is widely believed that in the absence of simplifying assumptions on the miscalibration, the only useful information in practice from the cardinal scores is the induced ranking. In this paper we address the fundamental question of whether this widespread folklore belief is actually true. We consider cardinal scores with arbitrary (or even adversarially chosen) miscalibrations that is only required to be consistent with the induced ranking. We design rating-based estimators and prove that despite making no assumptions on the ratings, they strictly and uniformly outperform all possible estimators that rely on only the ranking. These estimators can be used as a plug-in to show the superiority of cardinal scores over ordinal rankings for a variety of applications, including A/B testing and ranking. This work thus provides novel fundamental insights in the eternal debate between cardinal and ordinal data: It ranks the approach of using ratings higher than that of using rankings, and rates both approaches in terms of their estimation errors.
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Livingston, Miles, Andy Naranjo, and Lei Zhou. "Split bond ratings and rating migration." Journal of Banking & Finance 32, no. 8 (August 2008): 1613–24. http://dx.doi.org/10.1016/j.jbankfin.2007.11.019.
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Dijkers, Marcel, and Adam Stein. "Article 15: Comparing Verbal Rating Scale and Numeric Rating Scale Ratings of Pain." Archives of Physical Medicine and Rehabilitation 88, no. 10 (October 2007): e4. http://dx.doi.org/10.1016/j.apmr.2007.08.022.
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Daines, Robert M., Ian D. Gow, and David F. Larcker. "Rating the ratings: How good are commercial governance ratings?☆." Journal of Financial Economics 98, no. 3 (December 2010): 439–61. http://dx.doi.org/10.1016/j.jfineco.2010.06.005.
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Ruddy, John A. "An Analysis of Bank Financial Strength Ratings and Credit Rating Data." Risks 9, no. 9 (August 26, 2021): 155. http://dx.doi.org/10.3390/risks9090155.
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In this study, data from two credit rating agencies are analyzed to consider how different Bank Financial Strength Ratings and Credit Ratings from two rating agencies compare. To my knowledge, prior research has not analyzed Bank Financial Strength Ratings from different rating agencies, nor has it compared Bank Financial Strength Ratings to general credit ratings. These facts make this research unique. Univariate analyses are utilized to show relationships in the ratings data, along with parametric and non-parametric tests to make statistical inferences about the ratings data. There are five findings. First, ratings from different rating agencies are highly correlated. Second, different types of ratings from the same rating agency are highly correlated. Third, bank financial strength ratings are more conservative than credit ratings. Fourth, bank financial strength ratings declined in rating more quickly at the start of the financial crisis. Fifth, bank financial strength ratings from the Kroll Bond Rating Agency were more conservative than ratings from Moody’s Investors Service. The research findings and results are important for investors who consider ratings agency data to determine the risk of banking institutions. The results are also important to businesses that rely on bank credit rating data and policy makers who regulate banking institutions.
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Roch, Sylvia G., and Kimberly L. Braddock. "Do Employees Prefer to Receive Ratings? The Role of Justice Perceptions and Justice-Related Factors." Journal of Personnel Psychology 19, no. 3 (July 2020): 103–12. http://dx.doi.org/10.1027/1866-5888/a000243.
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Abstract. We empirically investigated whether employees would rather not receive performance ratings, as often claimed by those advocating the elimination of ratings. We also investigated whether rating preference is colored by perceived justice/injustice and whether factors antithetical to positive reactions to ratings – politics, low previous performance rating, and lack of a perceived link between ratings and outcomes – relate to employee rating preference. A survey of working adults indicated that most would rather receive ratings than not. The results also suggest that justice perceptions have a stronger influence on rating preference than injustice perceptions and that the perceived rating–outcome link has an especially robust relationship with rating preference.
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Peterson, Lindsay, John Bowblis, and Kathryn Hyer. "NH Compare’s Health Deficiency 5-Star Rating: Do We Learn Different Things From Survey and Complaint Deficiencies?" Innovation in Aging 4, Supplement_1 (December 1, 2020): 40. http://dx.doi.org/10.1093/geroni/igaa057.129.
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Abstract The Centers for Medicare and Medicaid Services (CMS) publishes a 5-star rating system for nursing homes (NH). Currently, the 5-star rating for health deficiencies weights deficiencies from annual recertification surveys and complaints equally. Complaint deficiencies may contain different information than survey deficiencies because complaint deficiencies originate with consumers and complaint inspections are less predictable than surveys. The objective of this study is to construct separate 5-star ratings for survey and complaint deficiencies, and to compare them to CMS’ 5-star rating for health deficiencies. Using CASPER and ASPEN Complaints/Incident Tracking System for all NHs in 2017 (N=15,373), we calculated the 5-star rating for health deficiencies as reported by CMS, and then decompose CMS’ rating into separate 5-star ratings for survey and complaint deficiencies. The overall distributions of the CMS’ deficiency rating and survey deficiency rating are similar. The distribution of the complaint deficiency rating is different from CMS’ deficiency rating. Using complaint deficiencies, more NHs have 5-stars (26.5% vs. 10.5%) and fewer facilities have 4-stars (11.2% vs. 23.3%). Comparing the ratings for each facility relative to CMS’ rating, 35.3% of NHs have a different survey deficiency rating while 54.4% have a different complaint deficiency rating. A 5-star rating based on survey and complaint deficiencies results in different ratings for NHs, indicating that complaint deficiency ratings contain different information from survey deficiency ratings. CMS should publish separate ratings based on survey and complaint deficiencies to provide different information.
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Myšková, Kateřina, and David Hampel. "Rating calibration." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 60, no. 2 (2012): 223–30. http://dx.doi.org/10.11118/actaun201260020223.
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In this work we deal with the question of whether the evaluation of selected rating agencies is equivalent in some sense or not and whether it is possible to find a relationship between assessments. The fact that rating agencies affect not only financial market participants (by publication of companies or states ratings) is undeniable. On the one hand, these agencies are criticized for the rating changes, which have influence for example credit conditions for rated entity. On the other hand, ratings have a growing number of users for which ratings have become one of the few clues in today’s complicated conditions powered by global financial crisis.For this purpose we use the calibration problem techniques, because calibration finds a relationship between two measurements, in our case between two independent assessments of rating agencies. Due to the nature of the data we assume that the relationship can be described by linear or quadratic function. So we use estimates derived for the one-dimensional linear calibration model with quadratic calibration function. This all we illustrate by the real ratings. The situation is complicated by the ordinal type data of the examined variables. Among other things, we discuss relations between ratings coming from particular rating agencies and evolution of this relation over time.
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Bartels, Bernhard. "Why rating agencies disagree on sovereign ratings." Empirical Economics 57, no. 5 (June 25, 2018): 1677–703. http://dx.doi.org/10.1007/s00181-018-1503-y.
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Kadariah, Siti, Anriza Witi Nasution, and Saparuddin Siregar. "Penerapan Konsep Peringkat Risiko pada Manajemen Risiko Hukum di Perbankan Syariah." Jurnal EMT KITA 7, no. 2 (March 1, 2023): 301–7. http://dx.doi.org/10.35870/emt.v7i2.890.
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This study aims to look at the risk rating, the risk rating is the final conclusion on the Bank's risk after considering the mitigation carried out through the implementation of risk management, to determine the bank's risk rating refers to the rating matrix. This matrix basically maps out risk ratings resulting from a combination of inherent risk and quality of risk management implementation. Research results determine the risk rating because the determination of the rating assessment is the basis for banks to categorize bank risk ratings. The results of applying risk ratings for banks are categorized into five ratings, namely, Low to moderate, Moderate, Moderate to high High, Low.
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Grudzevuch, Uljana. "Assessment of the activities of Ukrainian banks by rating agencies under the conditions of marital state." Economic Analysis, no. 33(1) (2023): 149–55. http://dx.doi.org/10.35774/econa2023.01.149.
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Introduction. The market of rating services is gradually developing both at the international and national levels. Over the years of operation of rating agencies, a significant number of various ratings have been developed and used. In particular, typical ratings are credit ratings of the issuer and debt obligations. One of the rating objects, along with countries, municipalities, large industrial enterprises, are banking institutions. If at the beginning of the activity of rating agencies in Ukraine, mainly banks with foreign capital and large banks had a rating, then in recent years all banks received a rating, which is one of the measures of their financial stability and reliability. At the same time, in recent years, in the conditions of the corona crisis, and currently in the conditions of martial law, the issues of expediency, objectivity and the need for rating assessment, including banks, have been actively raised, since there are significant differences in the assigned ratings on a national and international scale, and quite often, banks that received sufficiently high investment grade ratings from national rating agencies later became bankrupt. Purpose. Study of the main approaches and activities regarding the rating assessment of banks' activities by international and national rating agencies in the conditions of martial law. Methodology. On the basis of comparative and statistical analysis, a study of the rating assessment of the activity of banking institutions of Ukraine was carried out, the decisive factors influencing bank credit ratings and deposit reliability ratings were analyzed, the relationship between the sovereign rating of the country and the credit ratings of banks assigned by international rating agencies was determined. Results. The necessity of determining the ratings of banks, which act as an element of maintaining the reputation and image of the bank and provide an opportunity to enter international markets, attract investments, and also increase the level of awareness of clients about the financial condition and reliability of banks, has been proven. Emphasis is placed on the need to improve the legislative regulation of rating and unification of the methodology and scale of bank deposit reliability ratings.
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Niedziółka, Paweł. "The Country Ceiling and Sovereign Rating Relationship Exemplified by the Case of Poland." Acta Universitatis Lodziensis. Folia Oeconomica 3, no. 354 (July 8, 2021): 4–19. http://dx.doi.org/10.18778/0208-6018.354.01.
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The aim of the article is to answer the question whether the ratings of entities registered in Poland are limited by the sovereign rating of the country. The author theorises that the sovereign rating of Poland does not constitute the upper limit for ratings granted by the Big Three (Fitch Ratings, Moody’s and Standard & Poor’s) to Polish financial and non‑financial entities. The databases of three leading rating agencies were queried, selecting all (52) long‑term foreign ratings assigned to entities registered in Poland. The analysis indicates that currently no confirmation can be found of the use of the country ceiling principle, according to which the rating of any entity registered in a given country cannot be higher than its sovereign rating, by rating agencies (7.7% of rated entities in Poland is given higher rating than the sovereign one). This is at the same time a higher percentage than the average for all Big Three ratings, amounting to approx. 3%. The country ceiling is an upper, potential sovereign rating bound, resulting from the T&C risk. In the case of entities registered in Poland, however, their rating is a maximum of one notch higher than the sovereign rating, which in turn is in line with the policy that Standard & Poor’s officially announced as the only agency among the Big Three (the rating of an entity registered in a given jurisdiction can be up to four notches higher than the sovereign rating). The analysis of ratings assigned to Polish entities also indicates that a rating above the sovereign rating awarded by a given credit rating agency does not translate into similar actions of other agencies. This paper analyses the relationships between the concepts of country risk, T&C risk and sovereign risk. Another original contribution is establishing how the country ceiling principle used by rating agencies works in practice and verifying the scope of application of this principle in the Polish economic reality.
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White, Devin, Mingkang Wu, Ellen Novoseller, Vernon J. Lawhern, Nicholas Waytowich, and Yongcan Cao. "Rating-Based Reinforcement Learning." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 9 (March 24, 2024): 10207–15. http://dx.doi.org/10.1609/aaai.v38i9.28886.
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This paper develops a novel rating-based reinforcement learning approach that uses human ratings to obtain human guidance in reinforcement learning. Different from the existing preference-based and ranking-based reinforcement learning paradigms, based on human relative preferences over sample pairs, the proposed rating-based reinforcement learning approach is based on human evaluation of individual trajectories without relative comparisons between sample pairs. The rating-based reinforcement learning approach builds on a new prediction model for human ratings and a novel multi-class loss function. We conduct several experimental studies based on synthetic ratings and real human ratings to evaluate the effectiveness and benefits of the new rating-based reinforcement learning approach.
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Bae, Kee-Hong, Jun-Koo Kang, and Jin Wang. "Does Increased Competition Affect Credit Ratings? A Reexamination of the Effect of Fitch’s Market Share on Credit Ratings in the Corporate Bond Market." Journal of Financial and Quantitative Analysis 50, no. 5 (October 2015): 1011–35. http://dx.doi.org/10.1017/s0022109015000472.
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AbstractWe examine two competing views regarding the impact of competition among credit rating agencies on rating quality: the view that rating agencies do not sacrifice their reputation by inflating firm ratings, and the view that competition among rating agencies arising from the conflict of interest inherent in an “issuer pay” model creates pressure to inflate ratings. Using Fitch’s market share as a measure of competition among rating agencies and controlling for the endogeneity problem caused by unobservable industry effects, we find no relation between Fitch’s market share and ratings, suggesting that competition does not lead to rating inflation.
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Wang, Lu. "Bank Rating Gaps as Proxies for Systemic Risk." International Journal of Accounting and Financial Reporting 12, no. 2 (June 6, 2022): 1. http://dx.doi.org/10.5296/ijafr.v12i2.19678.
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Banks receive two types of ratings from major rating agencies: an “all-in” and a “stand-alone” rating. This paper investigates whether rating gaps between all-in ratings and stand-alone ratings could serve as a useful measure for the systemic risk of banks. Using US data from 1994 to 2007, the link between the rating gaps and a quantitative systemic risk measure, Co-independent Value at Risk (CoVar), is examined. The conclusion is that rating gaps are good proxies for systemic risk of large banks.
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Zhou, Xiangyun. "Can the dual-rating regulation improve the rating quality of Chinese corporate bonds?" PLOS ONE 16, no. 12 (December 2, 2021): e0259759. http://dx.doi.org/10.1371/journal.pone.0259759.
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We developed a dual-reputational rating shopping model to introduce public and institutional reputations. Investor’s and regulator’s penalty rates are described as public and institutional reputations, respectively. We achieved the available conditions of single-rating and dual-rating regulations to prevent rating inflation in this model. To examine the regulatory effects of different types of regulations on Chinese corporate bond ratings, we utilize panel ordered logit models. Theoretical analysis and empirical tests show that, when the reputation effect is low, the single-rating regulation is better at improving rating quality, and when the reputation effect is high, the dual-rating regulation induces rating agencies to provide more accurate ratings. Compared to the regulatory effects of the single-rating and the multi-rating regulations, the dual-rating regulation most effectively improves the rating quality of corporate bonds and prevents rating inflation.
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Lopatta, Kerstin, Magdalena Tchikov, and Finn Marten Körner. "The impact of market sectors and rating agencies on credit ratings: global evidence." Journal of Risk Finance 20, no. 5 (November 18, 2019): 389–410. http://dx.doi.org/10.1108/jrf-09-2017-0145.
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Purpose A credit rating, as a single indicator on one consistent scale, is designed as an objective and comparable measure within a credit rating agency (CRA). While research focuses mainly on the comparability of ratings between agencies, this paper additionally questions empirically how CRAs meet their promise of providing a consistent assessment of credit risk for issuers within and between market segments of the same agency. Design/methodology/approach Exhaustive and robust regression analyses are run to assess the impact of market sectors and rating agencies on credit ratings. The examinations consider the rating level, as well as rating downgrades as a further measure of empirical credit risk. Data stems from a large global sample of Bloomberg ratings from 11 market sectors for the period 2010-2018. Findings The analyses show differing effects of sectors and agencies on issuer ratings and downgrade probabilities. Empirical results on credit ratings and rating downgrades can then be attributed to investment grade and non-investment grade ratings. Originality/value The paper contributes to current finance research and practice by examining the credit rating differences between sectors and agencies and providing assistance to investors and other stakeholders, as well as researchers, how issuers’ sector and rating agency affiliations act as relative metrics.
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Vakilinia, Iman, Peyman Faizian, and Mohammad Mahdi Khalili. "RewardRating: A Mechanism Design Approach to Improve Rating Systems." Games 13, no. 4 (July 29, 2022): 52. http://dx.doi.org/10.3390/g13040052.
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Nowadays, rating systems play a crucial role in the attraction of customers to different services. However, as it is difficult to detect a fake rating, fraudulent users can potentially unfairly impact the rating’s aggregated score. This fraudulent behavior can negatively affect customers and businesses. To improve rating systems, in this paper, we take a novel mechanism-design approach to increase the cost of fake ratings while providing incentives for honest ratings. However, designing such a mechanism is a challenging task, as it is not possible to detect fake ratings since raters might rate a same service differently. Our proposed mechanism RewardRating is inspired by the stock market model in which users can invest in their ratings for services and receive a reward on the basis of future ratings. We leverage the fact that, if a service’s rating is affected by a fake rating, then the aggregated rating is biased toward the direction of the fake rating. First, we formally model the problem and discuss budget-balanced and incentive-compatibility specifications. Then, we suggest a profit-sharing scheme to cover the rating system’s requirements. Lastly, we analyze the performance of our proposed mechanism.
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Shmahelska, Marina. "World ratings: features of formation and impact on the on the country’s economic growth." Socio-Economic Research Bulletin, no. 2(77) (June 30, 2021): 181–92. http://dx.doi.org/10.33987/vsed.2(77).2021.181-192.
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The article investigates the ratings formation as a special type of activity that is actively implemented in a market economy. The process of creating a rating system is considered. It is established that the analysis results of economic entities activities are expressed as the results of evaluation in the rating scale. The main difference between the concepts of «rating» and «ranking» is determined, which allows building economic entities according to the ranking, that is, according to one of the indicators. The criteria that underlie the classification of ratings are analyzed. It is noted that in the economic literature, in most cases, it is carried out by rating agencies and companies. It is established that the rating process, as a business, has not only a methodological, but also a certain moral component. The regulatory element of rating agencies and features of their national and international rating scales are studied. A set (system) of national rating scales are determined, which provides the most complete and objective assessment of the issuer’s creditworthiness. The ratings of international rating agencies, which are assigned, usually, on two scales: international and national, are studied. It has been proven that changes in ratings play an important role for transactions with interest rate risks, as information for investors in decision making. The main methods of rating are established, which are largely closed. The leading credit ratings of international agencies, which are used by portfolio investors in decision-making, including country and regional ratings, are named. The main advantages that provide credibility to the ratings are substantiated, such as: the agency’s reputation; the agency has a generally recognized and accessible reporting methodology; differences in approaches to the analysis of rating subjects.
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McNabb, W. M., C. G. J. van den Berg, and S. R. Rimmer. "Comparison of inoculation methods for selection of plants resistant to Leptosphaeria maculans in Brassica napus." Canadian Journal of Plant Science 73, no. 4 (October 1, 1993): 1199–207. http://dx.doi.org/10.4141/cjps93-159.
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The relationship between ratings following four inoculation techniques and field ratings and the usefulness of these techniques for screening large populations was determined. Plants of Brassica napus ’Westar,’ ’Wesroona’, ’Topas’, ’Hanna’ and ’R8314’ were inoculated with L. maculans using four techniques: cotyledon inoculation with cotyledon rating, leaf inoculation with leaf and stem rating, stem inoculation with stem rating and inoculation using infested oat kernels with stem rating. Plants from each combination of cultivar and technique were self-pollinated for evaluation of disease rating in the field. The highest precision was obtained with cotyledon rating following cotyledon inoculation. The correlation coefficient between the rating of inoculated plants and the field rating of their progeny ranged from 0.50** for oat kernel inoculation to 0.72** for cotyledon inoculation. Considerable variation for field rating was associated with each rating following artificial inoculation. Selection of resistant plants using low cotyledon reaction was a more efficient technique than leaf or stem inoculation; it was rapid, required less labour and space and correlated well with the field ratings. Key words: Leptosphaeria maculans, Brassica napus, blackleg, oilseed rape, inoculation methods, canola
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Oehler, Andreas, Andreas Höfer, Matthias Horn, and Stefan Wendt. "Do mutual fund ratings provide valuable information for retail investors?" Studies in Economics and Finance 35, no. 1 (March 5, 2018): 137–52. http://dx.doi.org/10.1108/sef-05-2017-0120.
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Purpose Retail investors use information provided by mutual fund rating agencies to make investment decisions. This paper aims to examine whether the ratings provide useful information to retail investors by analyzing the rating migration and closure risk of mutual funds that received Morningstar’s mutual fund ratings from 2005 to 2012. Design/methodology/approach The research design differentiates between buy-and-hold investment strategies and dynamic investment strategies. To assess the information content of mutual fund ratings for buy-and-hold investment strategies, the rating migration based on the first and the last mutual fund rating during two-, four-, six- and eight-year horizons is determined. With respect to dynamic investment strategies, the number of rating changes per fund on a monthly basis during these time horizons is calculated. Findings Mutual fund rating persistence is low or even inexistent, in particular, during longer time periods. Only for lower-rated funds, the rating appears to indicate higher risk of fund closure. In addition, mutual funds face a large number of up to 38 monthly rating changes in the eight-year window. Originality/value Mutual fund rating persistence has hardly been analyzed for funds offered to retail investors so far. This paper clearly points out that because of the extensive rating migration and the high number of monthly rating changes, retail investors barely benefit from using mutual fund ratings.
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Li, Weiping. "Credit coordinate ratings with corresponding credit rating agencies and regulations." Journal of Financial Engineering 01, no. 01 (March 2014): 1450002. http://dx.doi.org/10.1142/s2345768614500020.
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This paper develops a coordinate rating for Credit Rating Agencies (CRAs) in the rating market. We first show that there is a necessary condition for the restructured sub-portfolios to have no-arbitrage principle for coordinate ratings. The coordinate rating is not only a natural extension of a single rating, but also reduces the rating bias and increases the rating accuracy. We solve the voluntary-disclosure decision problem for the issuer in terms of coordinate ratings. Furthermore, we show that the complexities of sub-portfolios do reduce the incentive to shop for the coordinate rating by comparing it with the incentive to shop for a single rating. The correlation among sub-portfolios also affect the incentive to shop in the coordinate rating. We advocate four principles for the credit rating system, from adapting coordinate ratings and reducing conflicts of interest to encouraging competition among CRAs and ensuring incentive alignment. We also build a model with disapproval correlation among CRAs and show that the probability of the joint disapproval is extremely sensitive to the disapproval correlation, even though the correlation may be very small in absolute value. Under an approval arrangement from the regulator in terms of the default rate within a CRA, we show that there exists a sub-game perfect equilibrium in which both approved CRAs provide correct coordinate ratings.
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Zhang, Qi, Longbing Cao, Chongyang Shi, and Liang Hu. "Tripartite Collaborative Filtering with Observability and Selection for Debiasing Rating Estimation on Missing-Not-at-Random Data." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 5 (May 18, 2021): 4671–78. http://dx.doi.org/10.1609/aaai.v35i5.16597.
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Most collaborative filtering (CF) models estimate missing ratings with an implicit assumption that the ratings are missing-at-random, which may cause the biased rating estimation and degraded performance since recent deep exploration shows that ratings may likely be missing-not-at-random (MNAR). To debias MNAR rating estimation, we introduce item observability and user selection to depict the generation of MNAR ratings and propose a tripartite CF (TCF) framework to jointly model the triple aspects of rating generation: item observability, user selection, and ratings, and to estimate the MNAR ratings. An item observability variable is introduced to a complete observability model to infer whether an item is observable to a user. TCF also conducts a complete rating model for rating generation and utilizes a user selection model dependent on the item observability and rating values to model user selection of the observable items. We further elaborately instantiate TCF as a Tripartite Probabilistic Matrix Factorization model (TPMF) by leveraging the probabilistic matrix factorization. Besides, TPMF introduces multifaceted dependency between user selection and ratings to model the influence of user selection on ratings. Extensive experiments on synthetic and real-world datasets show that modeling item observability and user selection effectively debias MNAR rating estimation, and TPMF outperforms the state-of-the-art methods in estimating the MNAR ratings.
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Schaffer, Elisabeth M., Ethan M. Basch, Gisela M. Schwab, and Antonia V. Bennett. "Comparison of weekly and daily recall of pain as an endpoint in a randomized phase 3 trial of cabozantinib for metastatic castration-resistant prostate cancer." Clinical Trials 18, no. 4 (April 22, 2021): 408–16. http://dx.doi.org/10.1177/17407745211009547.
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Introduction Scant evidence reveals whether the use of weekly versus daily pain ratings leads to meaningful differences when measuring pain as a clinical trial outcome. We compared the ability of weekly ratings and descriptors of daily ratings to evaluate pain as an endpoint in a randomized phase 3 drug trial. Methods Participants ( n = 119) with metastatic castration-resistant prostate cancer were randomized to treatment arms and rated their pain on the average and at its worst during a baseline week and at weeks 3, 6, and 12 of study treatment. For each reporting period, participants rated their pain daily for 7 days. On day 7, participants rated their pain over the prior 7 days. We estimated mean differences and intraclass correlation coefficients of the weekly ratings and the mean and the maximum daily ratings. We compared the ability of the weekly ratings and the daily rating descriptors to detect change in pain and evaluated the agreement of the weekly rating and the mean daily rating of pain at its worst to detect treatment response. Results For both pain constructs, the weekly rating was consistently higher than the mean daily rating and lower than the maximum daily rating yet was moderately to highly correlated with both daily rating descriptors (intraclass correlation coefficient range = 0.55–0.94). The weekly rating and the daily rating descriptors consistently detected change in pain for the study sample and participant subgroups. Substantial agreement existed between the weekly rating and the mean daily rating of pain at its worst when used with trial protocol opioid criteria to detect treatment response (Cohen’s κ = 0.71). Conclusion Use of daily over weekly ratings delivered no added benefit in evaluating pain in this clinical trial. This study is the first to compare weekly and daily recall to measure pain as an endpoint in a randomized phase 3 drug trial, and the pattern of differences in ratings that we observed is consistent with other recent evaluations of weekly and daily symptom reporting.
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Afonso, António, and André Albuquerque. "Sovereign Credit Rating Mismatches." Notas Económicas, no. 46 (July 1, 2018): 49–70. http://dx.doi.org/10.14195/2183-203x_46_3.
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We study the factors behind ratings mismatches in sovereign credit ratings from different agencies, for the period 1980‑‑2015. Using random effects ordered and simple probit approaches, we find that structural balances and the existence of a default in the last ten years were the least significant variables. In addition, the level of net debt, budget balances, GDP per capita and the existence of a default in the last five years were found to be the most relevant variables for rating mismatches across agencies. For speculative‑‑grade ratings, a default in the last two or five years decreases the rating difference between S&P and Fitch. For the positive rating difference between S&P and Moody’s, and for investment‑‑grade ratings, an increase in external debt leads to a smaller rating gap between the two agencies.
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Sandjaja, Stefanus Soejanto, Yuda Syahputra, and Lira Erwinda. "Validasi skala penilaian instrumen perencanaan karier menggunakan Andrich Threshold." Persona:Jurnal Psikologi Indonesia 9, no. 1 (June 29, 2020): 105–17. http://dx.doi.org/10.30996/persona.v9i1.3310.
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AbstractSuccess in a career is synonymous with the welfare of an individual's life, which needs further handling from the counselor. In determining and preparing for a future career, counselors should use a valid and reliable inventory. However, inventory that is considered valid and reliable by the counselor still raises problems in administration, namely students are confused in setting the response point in the inventory. The purpose of this study is to find a clear and unambiguous rating scale to make it easier for students to set a response point in their inventory. The research sample uses area random sampling consisting of six groups of test subjects, namely: 1, n = 75; 2, n = 61; 3, n = 47; 4, n = 146; 5, n = 85; and 6, n = 63. Data in this study were 5-point Likert scale political data collected using career planning inventory. The research data were analyzed using the Rasch model by testing the rating scale analysis through Threshold analysis between ratings. The results showed the rating scale in the Threshold analysis, the rating scale changed to a four-point Likert scale with a choice of very inappropriate, not appropriate, appropriate, and very appropriate.Keywords: Career Planning; Likert Scale; Ratting Scale; Threshold AbstrakSukses dalam karier identik dengan kesejahteraan hidup individu, yang perlu penanganan lebih lanjut dari konselor. Dalam menentukan dan mempersiapkan karier dimasa depan, konselor mestinya menggunakan inventori yang valid dan reliabel. Namun, inventori yang dianggap valid dan reliabel oleh konselor masih memunculkan permasalahan dalam pengadministrasian, yaitu siswa bingung dalam menetapkan rating scale pada inventori. Tujuan penelitian ini adalah menemukan skala penilaian yang jelas dan tidak ambigu untuk memudahkan siswa menetapkan rating scale pada inventori. Sampel penelitian menggunakan area random samplingyang terdiri dari enam kelompok subjek tes, yaitu: 1, n = 75; 2, n = 61; 3, n = 47; 4, n = 146; 5, n = 85; dan 6, n = 63. Data dalam penelitian ini berupa data politomi 5-point Likert scale yang dikumpulkan menggunakan career planning inventory. Data penelitian dianalisis menggunakan model Rasch dengan menguji rating scale analysis melalui analisis Threshold antar rating. Hasil penelitian menunjukkan rating scale pada analisis Threshold, rating scale berubah menjadi empat point Likert scale dengan pilihan sangat tidak sesuai, kurang sesuai, sesuai, dan sangat sesuai. Kata kunci: Perencanaan Karier; Ratting Scale; Skala Likert; Threshold
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deHaan, Ed. "The Financial Crisis and Corporate Credit Ratings." Accounting Review 92, no. 4 (January 1, 2017): 161–89. http://dx.doi.org/10.2308/accr-51659.
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ABSTRACT Credit ratings on many financial instruments failed to accurately portray default risk before the global financial crisis. I find no decline in the performance of corporate credit ratings during or after the crisis, indicating that the failures of ratings on financial instruments were due to conditions unique to the rating agencies' financial instruments divisions. Rather, the preponderance of tests indicate that corporate credit rating performance improves after the crisis, consistent with the rating agencies positively responding to public criticism and regulatory pressures. At the same time, I find evidence of sophisticated market participants decreasing their reliance on corporate credit ratings after the crisis. Consistent with theoretical models of reputation cyclicality, a likely explanation is that the rating agencies suffer spillover reputation damage from their failed ratings on financial instruments. My study informs regulators, practitioners, and academics about the performance of corporate credit ratings during and after the crisis, and provides novel empirical evidence consistent with reputation concerns affecting credit rating usage decisions.
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Kiesel, Florian, and Jonathan Spohnholtz. "CDS spreads as an independent measure of credit risk." Journal of Risk Finance 18, no. 2 (March 20, 2017): 122–44. http://dx.doi.org/10.1108/jrf-09-2016-0119.
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Purpose The creditworthiness of corporates is most visible in credit ratings. This paper aims to present an alternative credit rating measure independently of credit rating agencies. The credit rating score (CRS) is based on the credit default swap (CDS) market trading. Design/methodology/approach A CRS is developed which is a linear function of logarithmized CDS spreads. This new CRS is the first one that is completely independent of the rating agency. The estimated ratings are compared with ratings provided by Fitch Ratings for 310 European and US non-financial corporates. Findings The empirical analysis shows that logarithmized CDS spreads and issuer credit ratings by agencies have a linear relationship. The new CRS provides market participants with an alternative risk assessment, which is solely based on market factors, and does not rely on credit rating analysts. The results indicate that our CRS is able to anticipate agency ratings in advance. Moreover, the analysis shows that the trading volume has only a limited influence in the anticipation of rating changes. Originality/value This study shows a new approach to measure the creditworthiness of firms by analyzing CDS spreads. This is highly relevant for regulation, firm monitoring and investors.
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Mansoury, Masoud, Robin Burke, and Bamshad Mobasher. "Flatter Is Better." ACM Transactions on Intelligent Systems and Technology 12, no. 2 (March 2021): 1–16. http://dx.doi.org/10.1145/3437910.
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It is well known that explicit user ratings in recommender systems are biased toward high ratings and that users differ significantly in their usage of the rating scale. Implementers usually compensate for these issues through rating normalization or the inclusion of a user bias term in factorization models. However, these methods adjust only for the central tendency of users’ distributions. In this work, we demonstrate that a lack of flatness in rating distributions is negatively correlated with recommendation performance. We propose a rating transformation model that compensates for skew in the rating distribution as well as its central tendency by converting ratings into percentile values as a pre-processing step before recommendation generation. This transformation flattens the rating distribution, better compensates for differences in rating distributions, and improves recommendation performance. We also show that a smoothed version of this transformation can yield more intuitive results for users with very narrow rating distributions. A comprehensive set of experiments, with state-of-the-art recommendation algorithms in four real-world datasets, show improved ranking performance for these percentile transformations.
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Yao, Zhiyong, Dingwei Gu, and Yongmin Chen. "Rating deflation versus inflation: On procyclical credit ratings." Pacific-Basin Finance Journal 41 (February 2017): 46–64. http://dx.doi.org/10.1016/j.pacfin.2016.12.003.
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Bannier, Christina E., Patrick Behr, and Andre Güttler. "Rating opaque borrowers: why are unsolicited ratings lower?*." Review of Finance 14, no. 2 (November 14, 2009): 263–94. http://dx.doi.org/10.1093/rof/rfp025.
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Budsaratragoon, Pornanong, and Boonlert Jitmaneeroj. "Fund Ratings of Socially Responsible Investing (SRI) Funds: A Precautionary Note." Sustainability 13, no. 14 (July 6, 2021): 7548. http://dx.doi.org/10.3390/su13147548.
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We examine fund ratings of socially responsible investing (SRI) equity funds in emerging and developed markets by validating the assumptions of the equally weighted U.S. News mutual fund scorecard and the causal interrelations among its rating agencies—Morningstar, Lipper, Zacks, CFRA and TheStreet—for improvement priorities. In so doing, we apply a novel interdisciplinary methodology including cluster analysis, classification analysis, partial least squares structural equation modeling and importance performance analysis. We find evidence against the U.S. News assumptions, as individual rating agencies have unequal effects and exhibit the causal relationships among one another. We suggest emerging (developed) market fund managers allocate their resources—which are often limited—with the first priority to improving fund ratings of CFRA (Zacks), followed by Zacks (CFRA), TheStreet (Lipper), Lipper (Morningstar) and Morningstar (TheStreet). The positive causal relationships among rating agencies indicates that investors consider multiple rating agencies of the U.S. News for investment decisions, rather than simply use any single one of these rating agencies or their equally weighted aggregation. Interestingly, we find disagreement among rating agencies, with Zack (TheStreet) displaying rating deflation for emerging (developed) market funds. Disagreement among rating agencies may increase the monitoring effort of fund managers who usually “shop” for additional ratings in the hope of maximizing their average ratings.
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Pasricha, Puneet, Dharmaraja Selvamuthu, and Viswanathan Arunachalam. "Markov regenerative credit rating model." Journal of Risk Finance 18, no. 3 (May 15, 2017): 311–25. http://dx.doi.org/10.1108/jrf-09-2016-0123.
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Purpose Credit ratings serve as an important input in several applications in risk management of the financial firms. The level of credit rating changes from time to time because of random credit risk and, thus, can be modeled by an appropriate stochastic process. Markov chain models have been widely used in the literature to generate credit migration matrices; however, emergent empirical evidences suggest that the Markov property is not appropriate for credit rating dynamics. The purpose of this article is to address the non-Markov behavior of the rating dynamics. Design/methodology/approach This paper proposes a model based on Markov regenerative process (MRGP) with subordinated semi-Markov process (SMP) to obtain the estimates of rating migration probability matrices and default probabilities. Numerical example is given to illustrate the applicability of the proposed model with the help of historical Standard & Poor’s (S&P) credit rating data. Findings The proposed model implies that rating of a firm in the future not only depends on its present rating, but also on its previous ratings. If a firm gets a rating lower than its previous ratings, there are higher chances of further downgrades, and the issue is called the rating momentum. The model also addresses the ageing problem of credit rating evolution. Originality/value The contribution of this paper is a more general approach to study the rating dynamics and overcome the issues of inappropriateness of Markov process applied in rating dynamics.
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Jeong, Soohwan, Jeongseon Kim, Byung Suk Lee, and Sungsu Lim. "User tendency-based rating scaling in online trading networks." PLOS ONE 19, no. 4 (April 16, 2024): e0297903. http://dx.doi.org/10.1371/journal.pone.0297903.
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Social networks often involve the users rating each other based on their beliefs, abilities, and other characteristics. This is particularly common in e-commerce platforms where buyers rate sellers based on their trustworthiness. However, the rating tends to vary between users due to differences in their individual scoring criteria. For example, in a transaction network, a positive user may give a high rating unless the transaction was unsatisfactory while a neutral user may give a mid-rating, consequently giving the same numeric score to different levels of satisfaction. In this paper, we propose a novel method called user tendency-based rating scaling, which adjusts the current rating (its score) based on the pattern of past ratings. We investigate whether this rating scaling method can classify between “good users” and “bad users” in online trade social networks better when compared with using the original rating scores without scaling. Classifying between good users and bad users is especially important for anonymous rating networks like Bitcoin transaction networks, where users’ reputations must be recorded to preclude fraudulent and risky users. We evaluate the proposed rating scaling method by performing user classification, link prediction, and clustering tasks, using three real-world online rating network datasets. We use both the original ratings and the scaled ratings as weights of graphs and use a weighted graph embedding method to find node representations that reflect users’ positive and negative information. The experimental results showed that using the proposed rating scaling method outperformed using the original (i.e., unscaled) ratings by up to 17% in classification accuracy, and by up to 2.5% in link prediction based on the AUC ROC measure, and by up to 21% in the clustering tasks based on the Dunn-index.
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Labu, Yuliana Apriliani, Paulina Yuritha Amtiran, and Reyner F. Makatita. "PENGARUH MANAJEMEN LABA DAN RASIO KEUANGAN TERHADAP PERINGKAT OBLIGASI PERUSAHAAN MAKANAN DAN MINUMAN YANG TERDAFTAR DI BURSA EFEK INDONESIA." Journal of Management : Small and Medium Enterprises (SMEs) 17, no. 1 (March 1, 2024): 157–72. http://dx.doi.org/10.35508/jom.v17i1.13856.
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This study examines the effect of earnings management and financial ratios on bond ratings. The variables used are 1) The effect of earnings management on bond ratings, 2) The effect of liquidity ratio on bond rating, 3) The effect of activity ratio on bond rating, 4) The effect of solvency ratio on bond rating, 5) The effect of profitability ratio on bond rating. The samples used in the study based on criteria are food and beverage companies that have consecutive bond ratings from 2015 to 2020. From the results of purposive sampling logistic regression, which includes descriptive statistical tests, research model tests, and logistic regression tests. The results of hypothesis testing show that earnings management, liquidity ratio, and profitability ratio have no significant effect on bond ratings, while activity ratio and solvency ratio have a significant effect on bond ratings.
 Keywords: Earnings Management; Financial Ratio; Activity Ratio; Bond Rating; Liquidity Ratio, Profitability Ratio; Solvency Ratio
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Born, Patricia, Stephanie Müller, and Sharon Tennyson. "Credible or Biased?: An Analysis of Insurance Product Ratings in Germany." International Review of Financial Consumers 5, No. 1 Apr 2020 (July 1, 2020): 25–40. http://dx.doi.org/10.36544/irfc.2020.5-1.3.
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Instruments such as product ratings can help to overcome information asymmetries in retail financial markets. However, the capacity of ratings to promote market transparency and consumer awareness depends critically on whether they are credible. This article provides an empirical investigation of insurance product ratings in Germany, with an emphasis on the potential sources of bias that could undermine rating credibility. The analysis employs a panel dataset containing ratings for disability insurance products from two rating agencies over a 15-year period. Using the existing literature as a guide, we test a series of hypotheses regarding factors that may explain the variation in rating outcomes over time and across rating agencies. Our results suggest no major concerns regarding the credibility of insurance product ratings.
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Silveira, Rafaela Augusta Cunha, Renata Turola Takamatsu, and Bruna Camargos Avelino. "Impacto dos Ratings de crédito nas ações de empresas de capital aberto no Brasil." RACE - Revista de Administração, Contabilidade e Economia 16, no. 2 (August 30, 2017): 573–602. http://dx.doi.org/10.18593/race.v16i2.10556.
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Resumo O rating de crédito expressa uma opinião, por intermédio de escalas, sobre a qualidade do crédito de empresas, utilizado-a como medida de avaliação de risco no mercado. Agências de classificação de risco de crédito, como a Moody’s, divulgam os ratings que atribuem às empresas. Primeiramente, essas agências emitem o new rating, que representa o primeiro rating da companhia, e, posteriormente, essa emissão pode apresentar variações, denominadas upgrades e downgrades, relativas a boas e más notícias, respectivamente. Além disso, os ratings podem ser colocados em uma Watchlist quando, em breve, pode haver uma mudança do rating para downgrade ou para upgrade. O objetivo com este estudo consistiu, diante do que foi tratado, em abordar o impacto do rating de crédito sobre os preços das ações de empresas listadas na bolsa de valores brasileira. Para alcançar o objetivo proposto, foi analisada uma amostra de 44 empresas comercializadas na BM&FBovespa e 65 ratings nacionais de longo prazo emitidos pela Moody’s entre 2000 e 2015. Utilizou-se a metodologia de estudo de eventos, com os retornos normais calculados pelo modelo de retornos ajustados ao risco e ao mercado, e o Teste-F e o Teste-T para verificar a significância dos resultados. As análises finais evidenciaram que os preços das ações não são afetados de forma significativa pelas divulgações dos new ratings, downgrades, upgrades, on watch – possible downgrades e on watch – possible upgrades em nenhuma janela do evento, indicando que os ratings, para a amostra analisada, não trazem novas informações ao mercado.Palavras-chave: Ações. Rating. Estudo de eventos. Retornos anormais. Abstract Credit ratings are used as a mean to investors get new information on the companies by reducing the information asymmetry in the market. Thus, the rating is an important mean of business information with investors, enabling share prices relating to companies react to it. Branches of credit rating as Moody's, disclose the ratings they assign to companies. First, the agency issues the new rating, which represents the company's first rating, then this issue may vary, upgrades and downgrades calls relating to good and bad news respectively. In addition, the ratings could be placed in a Watchlist when, soon there may be a change to the rating downgrade or upgrade. The purpose of this study was to discuss the impact that the credit rating has on stock prices of companies listed on the Brazilian stock exchange. For a sample of 44 companies traded on BM&FBovespa and 65 long-term national ratings issued by Moody's between 2000 and 2015, we used the event study methodology, with normal returns calculated by the model of returns adjusted for risk and market the F-Test and T-Test to test the significance of the results. The final analysis showed that stock prices are not significantly affected by the disclosures of new ratings, downgrades, upgrades, on watch – possible downgrades and on watch – possible upgrades in any event window, indicating that the ratings do not bring new information to the market.Keywords: Stocks. Rating. Event studies. Abnormal returns.
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Arundina, Tika, and Dato’ Mohd Azmi Omar. "DETERMINANT OF SUKUK RATINGS." Buletin Ekonomi Moneter dan Perbankan 12, no. 1 (April 16, 2010): 97–114. http://dx.doi.org/10.21098/bemp.v12i1.468.
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With the development of sukuk market as the Islamic alternatives of the existing bond market, the issue of how to assign a rating to the sukuk issuance rises. This study tries to provide an empirical foundation for the investors to estimate the ratings assign. Using approach from several rating agencies, past researches on bond ratings, financial distress prediction and bankruptcy prediction models, this study is trying to innovate a new model on determining the sukuk ratings. It used Multinomial Logit regression to create a model of rating probability from several theoretical variables, ie. firm size, leverage, profitability, fixed payment coverage, reputation and existence of guarantor. The result shows 80% of all valid cases are correctly classified into their original rating classes.JEL Classification: C35, E43, P43Keywords: Sukuk, rating.
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Birtchnell, John. "Negative Modes of Relating, Marital Quality and Depression." British Journal of Psychiatry 158, no. 5 (May 1991): 648–57. http://dx.doi.org/10.1192/bjp.158.5.648.
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Young married couples, with or without a depressed wife, were divided into three groups according to marital quality. Negative modes of relating were assessed by self-rating and partner-rating questionnaires. The intercorrelation of scores for different modes of relating was higher on partner-rating than on self-rating scales. There was a significant gradient of mean negative-relating scores across the three levels of marital quality. The partner-ratings of depressives and their husbands were higher on all negative-relating scales than those of non-depressed women and their husbands. The self-ratings of the depressives corresponded with these negative ratings while those of their husbands did not. The partner-rating scores differentiated between the depressives with poor marriages and those with better marriages.
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Gupta, Rahul. "Financial Factors Determining CAREs Ratings." GIS Business 12, no. 6 (December 16, 2017): 34–42. http://dx.doi.org/10.26643/gis.v12i6.3310.
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Rating agencies evaluate a number of qualitative and quantitative factors while assigning rating to a particular company. Standard mathematical formulas do not exist for determining credit ratings. Instead, credit rating agencies use their experience and judgement in assigning ratings. What factors rating agencies consider significant in providing ratings to the companies is an important question. The present study aims to contribute to the above mentioned area by identifying the financial determinants of credit ratings assigned to Indian companies by CARE, one of the top rating agencies of India. Ordered probit analysis is used on unbalanced panel data with credit rating as the dependent categorical variable and six financial factors viz. size, liquidity, profitability, interest coverage, leverage, and growth as the independent variables. Results from ordered probit analysis indicate that the likelihood of credit ratings to be on higher side is more with increase of size, liquidity, profitability, interest coverage, growth and with a decrease in leverage. Further, size, profitability, and leverage are found to be statistically significant factors at the 1% level, liquidity and growth at the 5% level and interest coverage at the 10% level.
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HERZOG, SEBASTIAN, CHRISTIAN KOZIOL, and TIM THABE. "OPTIMAL CREDIT RATINGS." International Journal of Theoretical and Applied Finance 11, no. 02 (March 2008): 225–47. http://dx.doi.org/10.1142/s0219024908004786.
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In this paper, we show that an individual optimal credit rating exists for firms and empirically test whether firms strive to achieve their optimal rating. For this purpose, we consider the structural model by Leland [12], which balances the benefits of debt in the form of the tax-deductibility of interest payments against bankruptcy costs in order to obtain the optimal rating. Testable implications for both firms which have implemented their optimal rating and firms with non-optimal ratings are deduced. An empirical test with 420 firms contained in the S&P 500 Index indicates that all factors which theoretically drive optimal ratings also affect the observed rating in the predicted way. In line with our theory, observed ratings can be considerably better explained if, in addition to the traditional factors such as leverage and firm size, a proxy for bankruptcy costs and the default probability related to the optimal rating is considered. These findings suggest that U.S. firms contained in the S&P 500 Index strive to achieve their optimal credit ratings.
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Strausbaugh, Carl A., Anne M. Gillen, Stacey Camp, Clinton C. Shock, Eric P. Eldredge, and John J. Gallian. "Relationship of Beet Curly Top Foliar Ratings to Sugar Beet Yield." Plant Disease 91, no. 11 (November 2007): 1459–63. http://dx.doi.org/10.1094/pdis-91-11-1459.
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Sugar beet (Beta vulgaris) varieties were evaluated for disease resistance to curly top to establish if disease ratings made in inoculated nurseries correlated with disease ratings and yield in sugar beet crops exposed to natural disease outbreaks. Cultivars were planted both in inoculated curly top nurseries in Kimberly, ID, and in commercial cultivar trials in irrigated fields near Ontario, OR and Nampa, ID. Plants were evaluated for curly top using a rating scale of 0 (no symptoms) to 9 (dead). Moderate disease pressure in the Ontario (mean rating = 3.8) and Nampa (mean rating = 4.1) fields resulted in significant differences for disease rating, root yield, sugar content, and estimated recoverable sugar among cultivars. Disease ratings from both commercial fields were positively correlated (r = 0.91 and 0.82, P < 0.0001) with ratings from the inoculated nurseries. In commercial fields, root yield was negatively related to disease rating (r2 = 0.47 and 0.39, P ≤ 0.0004). For each unit increase in disease rating (increasing susceptibility), root yield decreased 5.76 to 6.93 t/ha. Thus, curly top nurseries reliably predict curly top resistant cultivars for commercial cultivation.
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Gholipour, Elnaz, Béla Vizvári, and Zoltán Lakner. "Reconstruction Rating Model of Sovereign Debt by Logical Analysis of Data." Mathematical Problems in Engineering 2021 (August 2, 2021): 1–11. http://dx.doi.org/10.1155/2021/2882930.
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Sovereign debt ratings provided by rating agencies measure the solvency of a country, as gauged by a lender or an investor. It is an indication of the risk involved in investment and should be determined correctly and in a well-timed manner. The current system is lacking transparency of rating criteria and mechanism. The present study reconstructs sovereign debt ratings through logical analysis of data (LAD), which is based on the theory of Boolean functions. It organizes groups of countries according to 20 World Bank-defined variables for the period 2012–2015. The Fitch Rating Agency, one of the three big global rating agencies, is used as a case study. An approximate algorithm was crucial in exploring the rating method, in correcting the agency’s errors, and in determining the estimated rating of otherwise unrated countries. The outcome was a decision tree for each year. Each country was assigned a rating. On average, the algorithm reached almost 98% matched ratings in the training set and was verified by 84% in the test set.
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Wang, Shihao, Yimin Yin, Jingran Wang, and Mengxia Wang. "Thermal rating probability prediction considering the temporal correlation among the thermal ratings." ITM Web of Conferences 47 (2022): 03020. http://dx.doi.org/10.1051/itmconf/20224703020.
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The thermal rating of the overhead transmission line is an important parameter for the operation and control of the power system. In order to further integrate it into the system dispatch decisions, it is necessary to conduct the prediction for the thermal ratings in the lookahead time horizon of dispatch decisions. At present, the researches on the thermal rating prediction focus on the independent prediction for the thermal rating in each prediction period, without considering the temporal correlation among the thermal ratings. In this paper, a joint probability prediction method for multiperiod thermal ratings considering the temporal correlation among the thermal ratings is proposed. Specifically, based on the temporal correlation among the thermal ratings and the independent probability prediction of thermal rating in each period, the multivariate normal probability density function of multiperiod thermal ratings is generated. The prediction simulation shows that considering the temporal correlation among the thermal ratings in the thermal rating prediction process can improve the prediction results and make full use of the currentcarrying capability of overhead lines, which will promote the accommodation of renewable energy and energy saving and emission reduction.
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Parnes, Dror, and Sagi Akron. "Rating the credit rating agencies." Applied Economics 48, no. 50 (April 21, 2016): 4799–812. http://dx.doi.org/10.1080/00036846.2016.1164826.
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Guo, Yiheng, Aza Azlina Md Kassim, and Kai Zhang. "Comparative Analysis of ESG Information Disclosures." Frontiers in Business, Economics and Management 8, no. 2 (April 6, 2023): 143–46. http://dx.doi.org/10.54097/fbem.v8i2.7130.
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ESG is a framework for the disclosure of non-financial information about companies, an investment philosophy and corporate evaluation criteria that focuses on non-financial performance. ESG ratings are a key part of ESG development, and the current number of global ESG rating agencies, with very different backgrounds and divergent ratings, makes it difficult to generate consensus on the ratings of the same subject. Therefore, on the basis of sorting out the situation of 11 famous ESG rating agencies and comparing and analyzing the ESG evaluation system of each rating agency, the study found that China's existing ESG rating system has core problems such as poor quality of information disclosure, inconsistent ESG rating results and imperfect ESG ecosystem, and accordingly put forward several suggestions for China's future ESG development.
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Miller, Caitlyn A., Nancy D. Albers-Miller, and Tami L. Knotts. "Applying television ratings to advertising: Are parents informed?" Young Consumers 19, no. 3 (August 20, 2018): 267–79. http://dx.doi.org/10.1108/yc-11-2017-00751.
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Purpose Both television and movie rating systems are used to inform parents, caregivers and prospective viewers about the content which will appear in a program. While rating systems are fallible, they do provide information prior to viewing. Unfortunately, television advertisements are not rated. Can a parent or caregiver feel confident that a child restricted to a particular level of viewing content will avoid being exposed to advertising content which exceeds the program rating? The purpose of this paper is to explore the content of advertisements relative to an established rating system. Design/methodology/approach Advertisements were assigned ratings based on the TV rating criteria. Comparisons between advertisement ratings and program ratings are provided. Additionally, advertisements are examined for unrated mature themes. Findings More than half of the advertisements analyzed across all program ratings were deemed appropriate for all audiences. However, it was discovered that advertisement content exceeded the content rating of the program during which it aired over 20 per cent of the time. Originality/value The findings show that the content of about one in every five television advertisements will have content that exceeds the content rating of the program in which the advertisement appears. This has the potential to undermine parental or caregiver restrictions on a child’s viewing content.
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Yurkov, A. V., and Zh R. Babaeva. "ESG-Ratings: Nonparametric Methods of Construction." Administrative Consulting, no. 2 (April 26, 2024): 92–107. http://dx.doi.org/10.22394/1726-1139-2024-2-92-107.
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Many of the largest Russian companies are evaluated by international financial institutions or rating agencies in terms of their influence on ESG factors that take into account environmental issues, interaction with society and corporate governance. Such ratings can have various names, most often referred to as ESG ratings. The inherent subjectivity of the assessments, along with the lack of generally recognized standards and transparency of the methodology, cause concern both from the assessed companies and from investors and regulators. ESG ratings of Russian rating agencies are at an early stage of their development, which is reflected in a small number of evaluated companies. The purpose of the study is to study the main methodological problems in the compilation of ESG ratings identified by the academic and business community with a focus on studying the issue of choosing weights when constructing a summary indicator. The information base of the study is the data published by the rating agency RAEX, which is positioned as the largest agency in the field of non-credit ratings. A comparative analysis of the rating agency’s weight selection methods with nonparametric methods, such as methods of shell analysis, determination of preferences based on similarity with the ideal solution and calculation of the geometric mean is carried out. Based on the results of the study of the initial data of the rating agency, it can be concluded that most companies have low ratings for the environmental component and high ratings for the corporate governance component, while none of the companies has a benchmark rating. The main methodological problem in the selection of weights is the subjective nature of the weights used by the rating agency. Correlation analysis of the studied non-parametric methods showed a high correlation with each other and with the initial ratings of the rating agency, however, at the level of some individual companies, the ratings may differ depending on the chosen method.
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Shamusarov, Sarvar. "WAYS TO IMPROVE UZBEKISTAN'S POSITION IN THE GLOBAL SOVEREIGN CREDIT RATING." Economics and education 24, no. 1 (February 28, 2023): 156–62. http://dx.doi.org/10.55439/eced/vol24_iss1/a22.
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In this article, the scientific-theoretical aspects of sovereign rating and loans and the financial-economic indicators affecting them are studied. Also, international rating agencies analyzed the practice of assessing Uzbekistan's sovereign credit rating and its position in international indexes and ratings in recent years, systematized negative factors affecting its position in ratings, and developed forecasts until 2024. As a result of the analysis, scientific proposals aimed at improving the position of our country in the Global sovereign credit rating were prepared
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Shimizu, Yoshiki, Junghee Lee, and Hideki Takei. "Analysis of Determinants of Split Ratings and Rating Conservativeness between Japanese and US Credit Rating Agencies." International Journal of Accounting and Financial Reporting 3, no. 1 (April 23, 2013): 182. http://dx.doi.org/10.5296/ijafr.v3i1.3507.
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In the previous paper, we confirmed the existence of the split ratings between Japanese and US credit rating agencies (CRAs). Our study did not support early studies suggesting that the split ratings were merely random occurrences. Rather, our findings suggested that the split ratings occurring between Japanese and US CRAs were not random and frequently occurring. The Japanese CRA assigned less conservative ratings than the US CRAs. In this paper, we performed the multivariate regression analysis to find variables which would differentiate the degree of rating conservativeness. Our samples were 192 Japanese companies which were assigned their ratings by Japanese and US credit rating agencies. We used 10-year bond ratings of these companies from 2000 and 2009. Our data sources were Nikkei NEEDS-Financial Quest for Japanese ratings and financial information and Thomson Reuters Datastream for US ratings. All financial data of the 192 firms were collected from Nikkei NEEDS-Financial Quest. According to our findings, Japanese agency seems to put higher weight on ROA than US agencies while all agencies seem to use variables such as asset, liquidity, and leverage to assign ratings. We assume that this is the main variable that has differentiated the degree of rating conservativeness.