Review of the literature on credit risk modeling : development of the past 10 years

This paper traces the developments of credit risk modeling in the past 10 years. Our work can be divided into two parts: selecting articles and summarizing results. On the one hand, by constructing an ordered logit model on historical Journal of Economic Literature (JEL) codes of articles about credit risk modeling, we sort out articles which are the most related to our topic. The result indicates that the JEL codes have become the standard to classify researches in credit risk modeling. On the other hand, comparing with the classical review Altman and Saunders(1998), we observe some important changes of research methods of credit risk. The main finding is that current focuses on credit risk modeling have moved from static individual-level models to dynamic portfolio models.

Modeling radionuclides dispersion and deposition downwind of a coal-fired power plant

In this study the inhalation doses and respective risk are calculated for the population living within a 20 km radius of a coal-fired power plant. The dispersion and deposition of natural radionuclides were simulated by a Gaussian dispersion model estimating the ground level activity concentration. The annual effective dose and total risk were 0.03205 mSv/y and 1.25 x 10-8, respectively. The effective dose is lower than the limit established by the ICRP and the risk is lower than the limit proposed by the U.S. EPA, which means that the considered exposure does not pose any risk for the public health.

MORM--a Petri net based model for assessing OH&S risks in industrial processes: modeling qualitative aspects.

Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.

Risk Mitigation Strategies for Operations and Maintenance Activities, Final Report, April 2012

The objective of this research was to investigate the application of integrated risk modeling to operations and maintenance activities, specifically moving operations, such as pavement testing, pavement marking, painting, snow removal, shoulder work, mowing, and so forth. The ultimate goal is to reduce the frequency and intensity of loss events (property damage, personal injury, and fatality) during operations and maintenance activities. This report includes a literature review that identifies the current and common practices adopted by different state departments of transportation (DOTs) and other transportation agencies for safe and efficient highway operations and maintenance (O/M) activities. The final appendix to the report includes information for eight innovative O/M risk mitigation technologies/equipment and covers the following for these technologies/equipment: Appropriate conditions for deployment Performance/effectiveness, depending on hazard/activity Cost to purchase Cost to operate and maintain Availability (resources and references)

Secondary Cancer Risk for Stage I Seminoma Patients - a Comparison of Adjuvant Treatment Versus Surveillance

Background: Post-surgical management of stage I seminoma includes: surveillance with repeated CT-scans and treatment reserved for those who relapse, or adjuvant treatment with either immediate radiation therapy (RT) or carboplatin. The cancer specific survival is close to 100%. Cure without long-term sequelae of treatment is the aim. Our goal is to estimate the risk of radiation-induced secondary cancers (SC) death from for patients undergoing S, adjuvant RT or adjuvant carboplatin (AC).Materials and Methods: We measured organ doses from CT scans (3 phases each one) of a seminoma patient who was part of the active surveillance strategy and from a man undergoing adjuvant RT 20-Gy and a 30-Gy salvage RT treatment to the para-aortic area using helical Intensity Modulated RT (Tomotherapy®) with accurate delineation of organs at risk and a CTV to PTV expansion of 1 cm. Effective doses to organs in mSv were estimated according to the tissue-weighting factors recommendations of the International Commission on Radiological Protection 103 (Ann ICRP 2007). We estimated SC incidence and mortality for a 10,000 people population based on the excess absolute risk model from the Biological Effects of Ionizing Radiation (BEIR) VII (Health Risk of Exposure to Low Levels of Ionizing Radiation, NCR, The National Academies Press Washington, DC, 2006) assuming a seminoma diagnosis at age 30, a total life expectancy of 80 years.Results: The nominal risk for a fatal secondary cancers was calculated 1.5% for 15 abdominal CT scans, 14.8% for adjuvant RT (20 Gy paraaortic field) and 22.2% for salvage RT (30 Gy). The calculation assumed that the risk of relapse on surveillance and adjuvant AC was 15% and 4% respectively and that all patients were salvaged at relapse with RT. n CT abdomen/Pelvis = secondary cancer % RT Dose and % receiving treatment = secondary cancer % Total secondary cancer risk in % Active surveillance 15 = 1.5% 30 Gy in 15% of pts = 3.3% 4.8 Adjuvant carboplatin 7 = 0.7% 30 Gy in 4% of pts = 0.88% 1.58 Adjuvant radiotherapy 7 = 0.7% 20 Gy in 100% of pts = 14.8% 15.5Conclusions: These data suggest that: 1) Adjuvant radiotherapy is harmful and should not anymore be regarded as a standard option for seminoma stage I. 2) AC seems to be an option to reduce radiation induced cancers. Limitations: the study does not consider secondary cancers due to chemotherapy with AC (unknown). The use of BEIR VII for risk modeling with higher doses of RT needs to be validated.

How Is Credit Risk Estimated? Discussion and Evidence based on Cross-Industry Sample Utilizing the KMV Model

The purpose of this thesis is to focus on credit risk estimation. Different credit risk estimation methods and characteristics of credit risk are discussed. The study is twofold, including an interview of a credit risk specialist and a quantitative section. Quantitative section applies the KMV model to estimate credit risk of 12 sample companies from three different industries: automobile, banking and financial sector and technology. Timeframe of the estimation is one year. On the basis of the KMV model and the interview, implications for analysis of credit risk are discussed. The KMV model yields consistent results with the existing credit ratings. However, banking and financial sector requires calibration of the model due to high leverage of the industry. Credit risk is considerably driven by leverage, value and volatility of assets. Credit risk models produce useful information on credit worthiness of a business. Yet, quantitative models often require qualitative support in the decision-making situation.

Risk of Agricultural Practices and Habitat Change to Farmland Birds

Many common bird species have declined as a result of agricultural intensification and this could be mitigated by organic farming. We paired sites for habitat and geographical location on organic and nonorganic farms in Ontario, Canada to test a priori predictions of effects on birds overall, 9 guilds and 22 species in relation to candidate models for farming practices (13 variables), local habitat features (12 variables), or habitat features that influence susceptibility to predation. We found that: (1) Overall bird abundance, but not richness, was significantly (p < 0.05) higher on organic sites (mean 43.1 individuals per site) than nonorganic sites (35.8 individuals per site). Significantly more species of birds were observed for five guilds, including primary grassland birds, on organic vs. nonorganic sites. No guild had higher richness or abundance on nonorganic farms; (2) Farming practice models were the best (ΔAIC < 4) for abundance of birds overall, primary grassland bird richness, sallier aerial insectivore richness and abundance, and abundance of ground nesters; (3) Habitat models were the best for overall richness, Neotropical migrant abundance, richness and abundance of Ontario-USA-Mexico (short-distance) migrants and resident richness; (4) Predation models were the best for richness of secondary grassland birds and ground feeders; (5) A combination of variables from the model types were best for richness or abundance overall, 13 of 18 guilds (richness and abundance) and 16 of 22 species analyzed. Five of 10 farming practice variables (including herbicide use, organic farm type) and 9 of 13 habitat variables (including hedgerow length, proportion of hay) were significant in best models. Risk modeling indicated that herbicide use could decrease primary grassland birds by one species (35% decline from 3.4 to 2.3 species) per site. Organic farming could benefit species of conservation concern by 49% (an increase from 7.6 to 11.4 grassland birds). An addition of 63 m of hedgerow could increase abundance and richness of short distance migrants by 50% (3.0 to 4.8 and 1.3 to 2.0, respectively). Increasing the proportion of hay on nonorganic farms to 50% could increase abundance of primary grassland bird by 40% (6.7 to 9.4). Our results provide support for alternative farmland designs and agricultural management systems that could enhance select bird species in farmland.

The Risk of Paradoxical Embolism (RoPE) Study: initial description of the completed database

BACKGROUND: Detecting a benefit from closure of patent foramen ovale in patients with cryptogenic stroke is hampered by low rates of stroke recurrence and uncertainty about the causal role of patent foramen ovale in the index event. A method to predict patent foramen ovale-attributable recurrence risk is needed. However, individual databases generally have too few stroke recurrences to support risk modeling. Prior studies of this population have been limited by low statistical power for examining factors related to recurrence. AIMS: The aim of this study was to develop a database to support modeling of patent foramen ovale-attributable recurrence risk by combining extant data sets. METHODS: We identified investigators with extant databases including subjects with cryptogenic stroke investigated for patent foramen ovale, determined the availability and characteristics of data in each database, collaboratively specified the variables to be included in the Risk of Paradoxical Embolism database, harmonized the variables across databases, and collected new primary data when necessary and feasible. RESULTS: The Risk of Paradoxical Embolism database has individual clinical, radiologic, and echocardiographic data from 12 component databases, including subjects with cryptogenic stroke both with (n = 1925) and without (n = 1749) patent foramen ovale. In the patent foramen ovale subjects, a total of 381 outcomes (stroke, transient ischemic attack, death) occurred (median follow-up 2·2 years). While there were substantial variations in data collection between studies, there was sufficient overlap to define a common set of variables suitable for risk modeling. CONCLUSION: While individual studies are inadequate for modeling patent foramen ovale-attributable recurrence risk, collaboration between investigators has yielded a database with sufficient power to identify those patients at highest risk for a patent foramen ovale-related stroke recurrence who may have the greatest potential benefit from patent foramen ovale closure.

Before and after modelling:risk knowledge management is required

Risk and knowledge are two concepts and components of business management which have so far been studied almost independently. This is especially true where risk management is conceived mainly in financial terms, as, for example, in the banking sector. The banking sector has sophisticated methodologies for managing risk, such as mathematical risk modeling. However. the methodologies for analyzing risk do not explicitly include knowledge management for risk knowledge creation and risk knowledge transfer. Banks are affected by internal and external changes with the consequent accommodation to new business models new regulations and the competition of big players around the world. Thus, banks have different levels of risk appetite and policies in risk management. This paper takes into consideration that business models are changing and that management is looking across the organization to identify the influence of strategic planning, information systems theory, risk management and knowledge management. These disciplines can handle the risks affecting banking that arise from different areas, but only if they work together. This creates a need to view them in an integrated way. This article sees enterprise risk management as a specific application of knowledge in order to control deviation from strategic objectives, shareholders' values and stakeholders' relationships. Before and after a modeling process it necessary to find insights into how the application of knowledge management processes can improve the understanding of risk and the implementation of enterprise risk management. The article presents a propose methodology to contribute to providing a guide for developing risk modeling knowledge and a reduction of knowledge silos, in order to improve the quality and quantity of solutions related to risk inquiries across the organization.

Credit risk & forward price models

Doutoramento em Gestão

Kreditrisiken - Modellierung und Management: Ein Überblick

Zusammenfassung Die Messung und Bewertung von Kreditrisiken stellt sich aktuell als ein sehr bedeutsames (Stichworte : Basel II, Solvency II, Kreditderivate) Gebiet dar. Allerdings hat sich hierbei keine einheitliche Vorgehensweise herausgebildet, sondern es existieren eine Vielzahl unterschiedlicher Ansatzpunkte und Modelle. Aus diesem Grund wird in dem vorliegenden Überblicksaufsatz versucht, einen systematischen Überblick über Problemfelder, Modellierungsansätze und Methoden des Risikomanagements im Kontext von Kreditrisiken zu geben. Nach einer einführenden Charakterisierung von Kreditrisiken und einem Abriss über Ratingsysteme werden zunächst die vier grundlegenden Kategorien von Kreditrisikomodellen (statische Modellierung der Ausfallverteilung, Unternehmenswertmodelle, Intensitätsmodelle und ratingbasierte Modelle) erörtert. Sodann erfolgt eine Darstellung der wichtigsten Industriemodelle (Credit Risk+, KMV, Credit Metrics, Credit Portfolio View). Behandelt werden ferner die Grundzüge von Basel II und die hierbei zugrunde liegende modelltheoretische Fundierung in Form von Einfaktormodellen sowie die Bewertung von ausfallbedrohten Zinstiteln. Abschließend wird auf Kreditderivate eingegangen.

Development of a Bayesian Joint Logistic Model to Better Study the Association between Haplotypes and Disease

In 2011, there will be an estimated 1,596,670 new cancer cases and 571,950 cancer-related deaths in the US. With the ever-increasing applications of cancer genetics in epidemiology, there is great potential to identify genetic risk factors that would help identify individuals with increased genetic susceptibility to cancer, which could be used to develop interventions or targeted therapies that could hopefully reduce cancer risk and mortality. In this dissertation, I propose to develop a new statistical method to evaluate the role of haplotypes in cancer susceptibility and development. This model will be flexible enough to handle not only haplotypes of any size, but also a variety of covariates. I will then apply this method to three cancer-related data sets (Hodgkin Disease, Glioma, and Lung Cancer). I hypothesize that there is substantial improvement in the estimation of association between haplotypes and disease, with the use of a Bayesian mathematical method to infer haplotypes that uses prior information from known genetics sources. Analysis based on haplotypes using information from publically available genetic sources generally show increased odds ratios and smaller p-values in both the Hodgkin, Glioma, and Lung data sets. For instance, the Bayesian Joint Logistic Model (BJLM) inferred haplotype TC had a substantially higher estimated effect size (OR=12.16, 95% CI = 2.47-90.1 vs. 9.24, 95% CI = 1.81-47.2) and more significant p-value (0.00044 vs. 0.008) for Hodgkin Disease compared to a traditional logistic regression approach. Also, the effect sizes of haplotypes modeled with recessive genetic effects were higher (and had more significant p-values) when analyzed with the BJLM. Full genetic models with haplotype information developed with the BJLM resulted in significantly higher discriminatory power and a significantly higher Net Reclassification Index compared to those developed with haplo.stats for lung cancer. Future analysis for this work could be to incorporate the 1000 Genomes project, which offers a larger selection of SNPs can be incorporated into the information from known genetic sources as well. Other future analysis include testing non-binary outcomes, like the levels of biomarkers that are present in lung cancer (NNK), and extending this analysis to full GWAS studies.