Ratingsysteme sind ein zentraler Bestandteil der Kreditrisikomodellierung. Neben der Bonitätsbeurteilung auf der Ebene der Kreditnehmer und der Risikoquantifizierung auf der Ebene der Ratingklassen spielt dabei die Bildung der Ratingklassen eine wesentliche Rolle. Die Literatur zur Ratingklassenbildung setzt auf modellfreie, in gewisser Weise willkürliche Optimierungsverfahren. Ein Ziel der vorliegenden Arbeit ist es, stattdessen ein parametrisches statistisches Modell zur Bildung der Ratingklassen einzuführen. Ein geeignetes Modell ist im Bereich der Bruchpunktschätzung zu finden. Dieses Modell und die in der mathematischen Literatur vorgeschlagenen Parameter- und Intervallschätzer werden in der vorliegenden Arbeit dargestellt und gründlich diskutiert. Dabei wird Wert auf eine anwendungsnahe und anschauliche Formulierung der mathematisch-statistischen Sachverhalte gelegt. Anschließend wird die Methodik der Bruchpunktschätzung auf einen konkreten Datensatz angewendet und mit verschiedenen anderen Kriterien zur Ratingklassenbildung verglichen. Hier erweist sich die Bruchpunktschätzung als vorteilhaft. Aufbauend auf der empirischen Untersuchung wird abschließend weiterer Forschungsbedarf abgeleitet. Dazu werden insbesondere Konzepte für den Mehrklassenfall und für abhängige Daten entworfen.:1. Einleitung 2. Ratingsystem 3. Bruchpunktschätzung 4. Anwendung 5. Zusammenfassung und Ausblick / Rating systems are a key component of credit risk modeling. In addition to scoring at borrowers’ level and risk quantification at the level of rating classes, the formation of the rating classes plays a fundamental role. The literature on rating classification uses in a way arbitrary optimization methods. Therefore, one aim of this contribution is to introduce a parametric statistical model to form the rating classes. A suitable model can be found in the area of split-point estimation. This model and the proposed parameter and interval estimators are presented and thoroughly discussed. Here, emphasis is placed on an application-oriented and intuitive formulation of the mathematical and statistical issues. Subsequently, the methodology of split-point estimation is applied to a specific data set and compared with several other criteria for rating classification. Here, split-point estimation proves to be advantageous. Finally, further research questions are derived on the basis of the empirical study. In particular, concepts for the case of more than two classes and for dependent data are sketched.:1. Einleitung 2. Ratingsystem 3. Bruchpunktschätzung 4. Anwendung 5. Zusammenfassung und Ausblick

Arctic Canada has seen significant ecological changes since the 1990s, leading to sea ice melt, increased temperatures, and increased accessibility to the Northwest Passage. The increased accessibility to the Northwest Passage has allowed for vessels to easily access maritime routes that were not previously accessible. Changes to the Arctic landscape has led to the beginning of open water shipping seasons in Arctic waters, attracting international audiences for trade, tourism, fisheries, and other economic activity. This new passageway increases options for companies to reduce costs in shipping, while also facilitating new and emerging hazards and risks for operational vessels. Comprehensive risk analysis and full assessments need to be completed to aid policy- and decision-makers to support and manage the increasing maritime traffic in Canadian Arctic waters. To fill this knowledge gap, the overarching aim of this master’s level research was to identify and preliminarily evaluate a comprehensive list of hazards (impact drivers) and risks (future impacts) for Maritime ship operations within Arctic Canada and to complete a preliminary assessment of identified maritime shipping hazards and risks throughout Arctic Canada. Hazards and risks were identified using several text-based sources, including social media, grey literature, and peer reviewed journal articles, in order to conduct a comprehensive content analysis to identify the perspectives and trends emerging among the online community. Natural language processing methods were then used, such as word frequencies, word correlation, and topic modelling to identify key phrases, terminology, and thematic groups. This allowed for the creation of an inventory of relevant hazard and risk themes and categories that could be used as a strong basis for informing a risk analysis. Emerging themes included: sea ice, navigability issues, geopolitical concerns, and operational challenges, among others. Following the identification of hazard and risk factors, a ‘failure modes, effects, and criticality analysis’ (FMECA) approach was used, along with a consequence-probability Rettinger ix matrix, as means of performing a preliminary risk analysis. The method enables the collection of information regarding hazard and risk descriptors, consequence, probability, control mechanisms, impacts, and data quality information, to establish a validated risk rating score. Risk rating scores are calculated using consequences and probability scores to determine average risk ratings for individual hazards and risks and at the sector-based category level. A total of 154 variables were inventoried: 55 hazards were identified and 99 risks were noted that influence maritime ship operations in Arctic Canada. Five variables were classified as ‘VERY HIGH’: three hazards (hydrocarbon releases, transportation of dangerous goods, and multiyear sea ice) and two risks (community member displacement and socioeconomic impacts on indigenous peoples). Five thematic groups were seen as priority risk ratings, two of which identified with “HIGH” data quality indexes (Sea Ice, Environmental). A total of 35 hazards and 36 risks are recommended for further investigation, being classified with a ‘VERY HIGH’ or ‘HIGH’ data quality score. Results of this research supports a preliminary attempt at a comprehensive risk analysis that can be used in the future to conduct a full risk assessment.

Financial sustainability is underrepresented in both the research on and practice of sustainability management and reporting. This article proposes a conceptual measure of financial sustainability and examines its association with capital market returns. The measure is positioned at the intersection of sustainability management, risk management and risk governance. Financial sustainability is regarded as a crucial control parameter complementing shareholder value and can be viewed by riskaverse investors as a secondary condition of investment decisions. It reduces refinancing and insolvency risks, leading to risk-adjusted excess returns in an imperfect capital market with financing restrictions and insolvency costs. We propose measuring a firm’s financial sustainability in terms of four conditions: (1) firm growth, (2) the company’s ability to survive, (3) an acceptable overall level of earnings risk exposure, and (4) an attractive earnings risk profile. We show that the application of a conditions-based investment strategy to European firms with high financial sustainability (i.e., firms fulfilling all four conditions) over the period from July 1990 to June 2019 results in monthly excess returns of 0.39%. This portfolio’s risk is lower than the risk of market investment. We find that the excess returns increase when incrementally adding each of the four conditions to the investment strategy.

[pt] Atualmente, com a intensificação da integração econômica e financeira dos mercados, o enfraquecimento das fronteiras nacionais e o significativo crescimento do comércio internacional, os investidores estão direcionando cada vez mais seus fluxos de capitais para os mercados externos, de forma a promover a diversificação internacional de suas carteiras, reduzindo o risco ao mesmo nível de retorno aos apresentados por carteiras puramente nacionais. É neste contexto de expansão internacional dos mercados e de elaboração de carteiras internacionais que as informações referentes aos riscos de cada investimento se tornam ainda mais importantes. Neste sentido, visando suprir essas necessidades de informações, começaram a surgir no início do século XX as empresas privadas de rating com o propósito de fornecer as classificações de risco dos emissores de títulos, os ratings de crédito. Consequentemente, ao classificar o risco de um título, esses ratings possuem a capacidade de influenciar o mercado como um todo. Assim, esse trabalho objetiva verificar o impacto que as alterações de rating soberano brasileiro pelas agências especializadas produzem no mercado acionário brasileiro, mais especificamente no comportamento das ações de empresas estatais, visto que estas deveriam ser supostamente mais impactadas que as demais frente a essas revisões, tanto via resposta do mercado como um todo quanto ao fato de ter a percepção do risco de seu controlador diretamente alterado por esses ratings. Para tanto, foi desenvolvido um estudo de evento, para analisar os efeitos verificados sobre os retornos de mercado (IBOVESPA) e das empresas estatais, nos períodos de downgrade e de upgrade. / [en] Currently, with the intensification of economic and financial integration of the markets, the weakening of national borders and the significant growth of international trade, investors are increasingly directing their capital flows towards external markets in order to promote international diversification of their portfolios, reducing the risk at the same level of return to those presented by purely domestic portfolios. It is in this context of international expansion of markets and of the development of international portfolios that the information regarding the risks of each investment becomes even more important. In this sense, in order to meet these information needs, the private rating companies began to emerge as early as the twentieth century, in order to provide risk ratings regarding the issuers of securities, credit ratings. Consequently, by classifying the risk of a security, these ratings have the ability to influence the market as a whole. Thus, this study aims to investigate the impact that Brazilian sovereign rating changes by these specialized agencies have in the Brazilian stock market, specifically regarding the behavior of shares of state-owned companies, as these should supposedly be more affected than the others against sovereign risk reviews, both through the market s response as a whole and by the fact that the perception of risk by their majority shareholder is directly altered by these ratings. To this end, an event study is conducted to analyze the effects seen on market returns (IBOVESPA) and state enterprises, in periods of downgrade and upgrade.

Objective: We consider the following problem from credit risk modeling: Our sample (Xi; Yi), 1 < i < n, consists of pairs of variables. The first variable Xi measures the creditworthiness of individual i. The second variable Yi is the default indicator of individual i. It has two states: Yi = 1 indicates a default, Yi = 0 a non-default. A default occurs, if individual i cannot meet its contractual credit obligations, i. e. it cannot pay back its outstandings regularly. In afirst step, our objective is to estimate the threshold between good and bad creditworthiness in the sense of dividing the range of Xi into two rating classes: One class with good creditworthiness and a low probability of default and another class with bad creditworthiness and a high probability of default. Methods: Given observations of individual creditworthiness Xi and defaults Yi, the field of change point analysis provides a natural way to estimate the breakpoint between the rating classes. In order to account for dependency between the observations, the literature proposes a combination of three model classes: These are a breakpoint model, a linear one-factor model for the creditworthiness Xi, and a Bernoulli mixture model for the defaults Yi. We generalize the dependency structure further and use a generalized link between systematic factor and idiosyncratic factor of creditworthiness. So the systematic factor cannot only change the location, but also the form of the distribution of creditworthiness. Results: For the case of two rating classes, we propose several estimators for the breakpoint and for the default probabilities within the rating classes. We prove the strong consistency of these estimators in the given non-i.i.d. framework. The theoretical results are illustrated by a simulation study. Finally, we give an overview of research opportunities.

In recent years, the emerging trends in cloud computing technologies have given rise to different computing services through the Internet. Organizations across the globe have seized this opportunity as a critical business driver for computing resource access and utilities that will indeed support significant business operations. Embracing SaaS as a crucial business factor enhances corporate business strategy through economies of scale, easy manageability, cost-effectiveness, non-geographical dependence, high reliability, flexible resources, and fast innovation. However, this has also come with various risks due to the limitation of traditional user identity and access control solutions’ inability to effectively identify and manage cloud users’ authorization process when interacting with the cloud. The limit can result in a legitimate user account's impersonation to carry out malicious activities after the user account is compromised to go undetected since traditional solutions seldom function based on user behavior trust level behind any account. Furthermore, the limitation is a significant vulnerability to the cloud environment. This vulnerability is known to be exploited by threats that can eventually lead to substantial unacceptable risks that can undermine security principles or requirements such as confidentiality, integrity, and availability. Significant consequences of this risk are categorized into financial damages, legal implications, reputational damages, and regulatory implications to the cloud environment. As a result, a solution that could contribute to the remediation of these potential risks incurred due to the limitation of user identity and access control management was proposed and designed as User Behavior Trust-Based Adaptive Security framework. The design aims to enhance how cloud users' identity and access control might be managed effectively based on a user behavior trust context and adaptation of corresponding access control measures through adaptive security. The design capability was manifested by integrating it into the standard ISO/2705:2018 Risk Management process. Although, there have been several good information security frameworks such as ISO/IEC 27005:2018 and other technical countermeasures such as SaaS Identity &amp; Access Management (IDaaS) to deal with this risk on the public cloud services. However, they are based on static mitigation approaches, so there is a solid need to shift towards a more dynamic strategical approach. The presented design work, User Behavior Trust-Based Adaptive Security framework, intends to serve as a proposed guideline for risk mitigation that would enhance user identity and access control limitations across the cloud. The solution functions by a trust modeling process that evaluates cloud user activities to compute a user behavior comprehensive trust degree. The resulting data is further used as input feeds parameters into a policy decision point process. The policy decision point process adapts the input parameters to user behavior trust level and behavior risk rating to determine the appropriate access control decision. Ultimately, the adaptive security solution consults the policy decision points to dynamically enforce the corresponding controls measures based on the access control decision received as input feed. The report also conducts a risk assessment process to identify vulnerabilities, threats, and risks related to user behavior trust level and risk rating regarding SaaS resources. Then adapt the mitigation solution, User Behavior Trust-Based Adaptive Security framework, as a possible risk treatment within the risk management process ISO/2705:2018. This report uses a design methodology derived from User Behavior Trust Modelling scientific research work, Gartner Adaptive Security Architecture Model, and eXtensible Access Control Markup Language's policy decision point concept. The design evaluates user behavior trust level by the trust modeling, while the integrated policy decision point processes the trust level to make the access control decision which is later enforced by the adaptive security solution. The report further adapts the risk management procedure ISO/2705:2018 to identify risk from user behavior and trust level, then implements the design solution as a possible risk treatment. The research findings were documented as Results and Discussion, where the functional and operational aspects of the designed framework were provided. In addition, the effects of applying the framework as a possible risk treatment solution were observed through conducting an ISO/2705:2018 risk management procedure. The notable outcome of a reduction of identified risk levels was an improvement in user attitude or behavior, which eventually increased user behavior trust level and reduced associated behavior risk. At the same time, the discussion detailed the interpretation of the results, implications, and limitation of the research, why the framework could be considered a remediation solution beyond the state-of-the-art for cloud user identity and access management—precisely by integrating user behavior, trust, policy decision making with adaptive security into risk management process to reduce IDM-associated risk in the SaaS. Finally, this study has outlined the significance of adopting the designed framework as a possible mitigation solution to enhance the shortcomings of user identity and access control management in the cloud. It has demonstrated that SaaS identified risk can be reduced to an acceptable level when user behavior and activities are taken seriously. Insight into the current trust state and associated risk level of cloud users are vital for continuous risk monitoring and reduction. The solution is to be used as a recommended guideline that might significantly contribute to the research community and information security field of cloud security. Future research direction to consider the possibility of simulating and transforming this conceptual and abstract framework into a real-world working solution due to research work limitations. The framework was designed based on recognized and accepted scientific and technological principles and concepts, from user behavior trust modeling, eXtensible access control markup language, and adaptive security architecture. In addition, to extend this concept to a future research area that will focus exclusively on application-processes behavior.