SVDD: A proposal for automated credit rating prediction

Gangolf, Claude; Dochow, Robert; Schmidt, Günter; Tamisier, Thomas

doi:10.1109/codit.2014.6996866

Cited by 7 publications

(2 citation statements)

References 10 publications

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“…Изменение кредитного качества участников финансового рынка является важным критерием при определении направлений инвестирования (Becker, Milbourn, 2010;Gangolf, Dochow, Schmidt, Tamisier, 2014;Wang, Carson, 2014;An, Nichols, 2014). Как упоминалось во введении, рейтинговое агентство Moody's ввело 2 индикатора: рейтинговая активность и рейтинговый дрифт.…”

Section: рейтинговая активность и рейтинговый дрифтunclassified

О Двух Индексах Изменения Рыночного Состояния На Основе Матриц Рейтинговых Миграций

Irmatova¹

2015

Global Markets and Financial Engineering

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Статья посвящена исследованию рейтинговых изменений в условиях кризисных тенденций на рынке с помощью матриц вероятностей рейтинговых переходов. Автором была выявлена необходимость разработки инструмента индицирования негативных рыночных явлений, основанная на невозможности расчета существующих индикаторов рейтингового агентства Moody’s Investors Service широким кругом лиц. В статье вводятся два новых индекса, миграционный дрифт и усложненный дрифт, для анализа кредитного качества рынка и его участников, построенные на базе матриц рейтинговых миграций. Делается акцент на возможности их использования всеми заинтересованными лицами. На основании тестирования индексов устанавливается, что созданные индикаторы имеют предсказательную силу, не уступающую показателям Moody’s, и даже позволяют улучшить их показания в определенных моментах.

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Section: рейтинговая активность и рейтинговый дрифтunclassified

О Двух Индексах Изменения Рыночного Состояния На Основе Матриц Рейтинговых Миграций

Irmatova¹

2015

Global Markets and Financial Engineering

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“…These studies were criticized for the fact that CRAs used non-public data and rated subjective evaluations in their methodologies. The statistical models used by the CRAs for credit rating have been examined and alternative models have been proposed [6,15,17,[29][30][31]33]. In this study, we propose alternative models to sovereign credit rating methods that classify countries as investable or speculative.…”

Section: Introductionmentioning

confidence: 99%

Novel Approaches on Sovereign Credit Ratings

Önal

Karaçuha²

2018

Eur. J. Pure Appl. Math.

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Credit ratings that are transparent, impartial and reliable as well as being up to date, quickly and easily calculated will provide convenience to investors and countries. In this study, sovereign credit rating methodologies of CRAs and studies in relevant literature are examined in detail, and two dynamic methods are proposed. These models classify countries as investable or speculative in the short term. In the first model, we used stock market values and macroeconomic variables with the Normalized Least Mean Square (NLMS) algorithm. Ratings for 15 countries are determined according to the short-term domestic currency. The results that we obtained from this model are fully consistent with those of Fitch. When we compared the results with Standard and Poor’s, we obtained different results for Turkey and Portugal. In the second model, we used only stock market closing data from 40 composite indexes with the Artificial Neural Networks (ANNs). Ratings are determined according to short-term foreign currency. The results that we acquired from these two models are fully compliant with Standard and Poor's. However, when compared to the ratings of Fitch, the results differed in the case of Russia. It has been shown that contrary to standard approaches, high predictability is achievable for countries using short-term data. The suggested models are more objective and dynamic due to only short-term data being required.

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Automated Credit Rating Prediction in a competitive framework

et al. 2016

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Automated credit rating prediction (ACRP) algorithms are used to predict the ratings of bonds without having to trust one rating agency, like Moody's, Fitch or S&P. Nevertheless, for the moment, the accuracy of ACRP algorithms is investigated by empirical tests. In this paper, the framework for a competitive analysis is set and afterwards in this framework, the definition of competitive ACRP algorithms and its demonstration is given. In this way, for a competitive ACRP algorithm, a worst-case guarantee concerning the misclassification error is offered. Furthermore, several ACRP algorithms from the literature are compared according their competitiveness.

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SVDD: A proposal for automated credit rating prediction

Cited by 7 publications

References 10 publications

О Двух Индексах Изменения Рыночного Состояния На Основе Матриц Рейтинговых Миграций

О Двух Индексах Изменения Рыночного Состояния На Основе Матриц Рейтинговых Миграций

Novel Approaches on Sovereign Credit Ratings

Automated Credit Rating Prediction in a competitive framework

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