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Risk Models (risk + models)
Selected AbstractsCredit Risk Models , Do They Deliver Their Promises?ECONOMIC NOTES, Issue 2 2003A Quantitative Assessment We develop a framework to assess the statistical significance of expected default frequency calculated by credit risk models. This framework is then used to analyse the quality of two commercially available models that have become popular among practitioners: KMV Credit Monitor and RiskCalc from Moody's. Using a unique database of expected default probability from both vendors, we study both the consistency of the prediction and its timeliness. We introduce the concept of cumulative accuracy profile (CAP) that allows to see in one curve the percentage of defaulting companies captured by the models one year in advance. We also use the Miller's information test to see if the models add information to the S&P rating. The result of the analysis indicates that these models indeed add relevant information not accounted for by rating alone. Moreover, with respect to rating agencies, the models predict defaults more than ten months in advance on average. (J.E.L.: C52). [source] PEL: an unbiased method for estimating age-dependent genetic disease risk from pedigree data unselected for family historyGENETIC EPIDEMIOLOGY, Issue 5 2009F. Alarcon Abstract Providing valid risk estimates of a genetic disease with variable age of onset is a major challenge for prevention strategies. When data are obtained from pedigrees ascertained through affected individuals, an adjustment for ascertainment bias is necessary. This article focuses on ascertainment through at least one affected and presents an estimation method based on maximum likelihood, called the Proband's phenotype exclusion likelihood or PEL for estimating age-dependent penetrance using disease status and genotypic information of family members in pedigrees unselected for family history. We studied the properties of the PEL and compared with another method, the prospective likelihood, in terms of bias and efficiency in risk estimate. For that purpose, family samples were simulated under various disease risk models and under various ascertainment patterns. We showed that, whatever the genetic model and the ascertainment scheme, the PEL provided unbiased estimates, whereas the prospective likelihood exhibited some bias in a number of situations. As an illustration, we estimated the disease risk for transthyretin amyloid neuropathy from a French sample and a Portuguese sample and for BRCA1/2 associated breast cancer from a sample ascertained on early-onset breast cancer cases. Genet. Epidemiol. 33:379,385, 2009. © 2008 Wiley-Liss, Inc. [source] Review and comparison between the Wells,Riley and dose-response approaches to risk assessment of infectious respiratory diseasesINDOOR AIR, Issue 1 2010G. N. Sze To Abstract, Infection risk assessment is very useful in understanding the transmission dynamics of infectious diseases and in predicting the risk of these diseases to the public. Quantitative infection risk assessment can provide quantitative analysis of disease transmission and the effectiveness of infection control measures. The Wells,Riley model has been extensively used for quantitative infection risk assessment of respiratory infectious diseases in indoor premises. Some newer studies have also proposed the use of dose-response models for such purpose. This study reviews and compares these two approaches to infection risk assessment of respiratory infectious diseases. The Wells,Riley model allows quick assessment and does not require interspecies extrapolation of infectivity. Dose-response models can consider other disease transmission routes in addition to airborne route and can calculate the infectious source strength of an outbreak in terms of the quantity of the pathogen rather than a hypothetical unit. Spatial distribution of airborne pathogens is one of the most important factors in infection risk assessment of respiratory disease. Respiratory deposition of aerosol induces heterogeneous infectivity of intake pathogens and randomness on the intake dose, which are not being well accounted for in current risk models. Some suggestions for further development of the risk assessment models are proposed. Practical Implications This review article summarizes the strengths and limitations of the Wells,Riley and the dose-response models for risk assessment of respiratory diseases. Even with many efforts by various investigators to develop and modify the risk assessment models, some limitations still persist. This review serves as a reference for further development of infection risk assessment models of respiratory diseases. The Wells,Riley model and dose-response model offer specific advantages. Risk assessors can select the approach that is suitable to their particular conditions to perform risk assessment. [source] An Empirical Assessment of Country Risk Ratings and Associated ModelsJOURNAL OF ECONOMIC SURVEYS, Issue 4 2004Suhejla Hoti Abstract., Country risk has become a topic of major concern for the international financial community over the last two decades. The importance of country ratings is underscored by the existence of several major country risk rating agencies, namely the Economist Intelligence Unit, Euromoney, Institutional Investor, International Country Risk Guide, Moody's, Political Risk Services, and Standard and Poor's. These risk rating agencies employ different methods to determine country risk ratings, combining a range of qualitative and quantitative information regarding alternative measures of economic, financial and political risk into associated composite risk ratings. However, the accuracy of any risk rating agency with regard to any or all of these measures is open to question. For this reason, it is necessary to review the literature relating to empirical country risk models according to established statistical and econometric criteria used in estimation, evaluation and forecasting. Such an evaluation permits a critical assessment of the relevance and practicality of the country risk literature. The paper also provides an international comparison of risk ratings for twelve countries from six geographic regions. These ratings are compiled by the International Country Risk Guide, which is the only rating agency to provide detailed and consistent monthly data over an extended period for a large number of countries. The time series data permit a comparative assessment of the international country risk ratings, and highlight the importance of economic, financial and political risk ratings as components of a composite risk rating. [source] Aortic Stenosis: Assessment of the Patient at RiskJOURNAL OF INTERVENTIONAL CARDIOLOGY, Issue 6 2007KHUNG KEONG YEO M.B.B.S. The true incidence of aortic stenosis among the general population is unknown but aortic sclerosis, its precursor, has been estimated to affect about 25% of people over age 65, while an estimated 3% of the population over age 75 have severe aortic stenosis. Severe aortic stenosis, when accompanied by symptoms of angina, syncope, or heart failure, is associated with high mortality rates. Two-dimensional and Doppler echocardiography are cornerstone tools for the evaluation and monitoring of aortic stenosis. Echocardiography helps identify the patient at risk of death and guide timing of aortic valve replacement. Other important diagnostic tools include cardiac catheterization, treadmill stress testing, and dobutamine stress echocardiography, although their use is limited to specific patient populations. Aortic valve replacement carries a significant operative risk of approximately 4.0%. However, risk of operative mortality varies according to comorbidities and disease presentation. There are many risk models that guide estimation of the risk of operative mortality. Understanding operative risk is important in patient care and the selection of patients for aortic valve replacement. [source] Risk factors for venous thrombosis in medical inpatients: validation of a thrombosis risk scoreJOURNAL OF THROMBOSIS AND HAEMOSTASIS, Issue 12 2004N. A. Zakai Summary.,Background/objectives:,The occurrence of and risk factors for venous thrombosis (VT) complicating hospital admission in unselected medical inpatients have not been widely studied. Patients and methods:,In a 400-bed teaching hospital we identified all cases of VT complicating hospital admission between September 2000 and September 2002 using discharge codes and chart review. Controls were randomly selected adult inpatients frequency matched to cases for medical service. Results:,The incidence of VT complicating hospital admission was 7.6 per 1000 admissions. On average, VT was diagnosed on the fifth hospital day. The median age of the 65 cases and 123 controls was 68 years and 45% were men. Cases had a 4-fold higher death rate than controls [95% confidence interval (CI) 1.9, 8.8]. At admission, trauma within 3 months, leg edema, pneumonia, platelet count > 350 × 103 mm,3 and certain cancers were associated with risk of VT. Age, body mass index, and acute myocardial infarction were not associated with VT risk. One of three published VT risk models was able to risk stratify patients and was associated with a 2.6-fold increased risk of VT (95% CI 1.3, 5.5). Use of VT prophylaxis did not differ in cases and controls; prophylaxis was used <,1/3 of hospital days in 52% of patients. Conclusions:,VT was common among medical inpatients. Of the risk factors identified, elevated platelet count has not been previously reported. Only one of three published risk scores was associated with risk of inpatient VT. Future study should improve upon risk prediction models for in-hospital VT among medical patients. [source] Is it effective to target treatment using just calculated CHD risk?PRESCRIBER, Issue 14 2010FRCPath, Tim Reynolds BSc Statin prescribing for the primary prevention of CHD is based on risk calculated from long-term population data. Here, the author discusses the issues with the current risk models and suggests that money could be better spent on improved targeting through the use of a diagnostic test. Copyright © 2010 Wiley Interface Ltd [source] How Accurate Are Value-at-Risk Models at Commercial Banks?THE JOURNAL OF FINANCE, Issue 3 2002Jeremy Berkowitz In recent years, the trading accounts at large commercial banks have grown substantially and become progressively more diverse and complex. We provide descriptive statistics on the trading revenues from such activities and on the associated Value-at-Risk (VaR) forecasts internally estimated by banks. For a sample of large bank holding companies, we evaluate the performance of banks' trading risk models by examining the statistical accuracy of the VaR forecasts. Although a substantial literature has examined the statistical and economic meaning of Value-at-Risk models, this article is the first to provide a detailed analysis of the performance of models actually in use. [source] Subgroup Analyses in Randomized Controlled Trials: The Need for Risk Stratification in Kidney TransplantationAMERICAN JOURNAL OF TRANSPLANTATION, Issue 10 2009M. Wagner Although randomized controlled trials (RCT) are the gold standard for establishing causation in clinical research, their aggregated results can be misleading when applied to individual patients. A treatment may be beneficial in some patients, but its harms may outweigh benefits in others. While conventional one-variable-at-a-time subgroup analyses have well-known limitations, multivariable risk-based analyses can help uncover clinically significant heterogeneity in treatment effects that may be otherwise obscured. Trials in kidney transplantation have yielded the finding that a reduction in acute rejection does not translate into a similar benefit in prolonging graft survival and improving graft function. This paradox might be explained by the variation in risk for acute rejection among included kidney transplant recipients varying the likelihood of benefit or harm from intense immunosuppressive regimens. Analyses that stratify patients by their immunological risk may resolve these otherwise puzzling results. Reliable risk models should be developed to investigate benefits and harms in rationally designed risk-based subgroups of patients in existing RCT data sets. These risk strata would need to be validated in future prospective clinical trials examining long-term effects on patient and graft survival. This approach may allow better individualized treatment choices for kidney transplant recipients. [source] Robust Tests for Single-marker Analysis in Case-Control Genetic Association StudiesANNALS OF HUMAN GENETICS, Issue 2 2009Qizhai Li Summary Choosing an appropriate single-marker association test is critical to the success of case-control genetic association studies. An ideal single-marker analysis should have robust performance across a wide range of potential disease risk models. MAX was designed specifically to achieve such robustness. In this work, we derived the power calculation formula for MAX and conducted a comprehensive power comparison between MAX and two other commonly used single-marker tests, the one-degree-of-freedom (1-df) Cochran-Armitage trend test and the 2-df Pearson ,2 test. We used a single-marker disease risk model and a two-marker haplotype risk model to explore the performances of the above three tests. We found that each test has its own "sweet" spots. Among the three tests considered, MAX appears to have the most robust performance. [source] Upper bounds for ruin probabilities in two dependent risk models under rates of interestAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 4 2010Dingjun Yao Abstract In this article, we consider two discrete-time risk models, in which dependent structures of the payments and the interest force are considered. Two autoregressive moving-average (ARMA) models are introduced to model the premiums and rates of interest, and the claims are assumed to be independent. Generalized Lundberg inequalities for the ruin probabilities are derived by using renewal recursive technique, which extend some known results. Copyright © 2009 John Wiley & Sons, Ltd. [source] Asymptotic behaviour of the finite-time ruin probability in renewal risk modelsAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 3 2009Remigijus Leipus Abstract In this paper we study the tail behaviour of the probability of ruin within finite time t, as initial risk reserve x tends to infinity, for the renewal risk model with strongly subexponential claim sizes. The asymptotic formula holds uniformly for t,[f(x), ,), where f(x) is an infinitely increasing function, and substantially extends the result of Tang (Stoch. Models 2004; 20:281,297) obtained for the class of claim distributions with consistently varying tails. Two examples illustrate the result. Copyright © 2008 John Wiley & Sons, Ltd. [source] Tail equivalence relationships for ruin probabilities in several risk modelsAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 6 2005Feng Hu Abstract This paper is a further investigation into the ruin probability ,(x) in several risk models, where x is the initial surplus. Under the assumption that the claim sizes are heavy-tailed, we get some tail equivalence relationships of ,(x). Copyright © 2005 John Wiley & Sons, Ltd. [source] Semiparametric competing risks analysisTHE ECONOMETRICS JOURNAL, Issue 2 2007José Canals-Cerdá Summary, In this paper we analyse a semi-parametric estimation technique for competing risks models based on series expansion of the joint density of the unobserved heterogeneity components. This technique allows for unrestricted correlation among the risks. The finite sample behavior of the estimation technique is analysed in a Monte Carlo experiment using an empirically relevant data-generating process. The estimator performs well when compared with the Heckman,Singer estimator. [source] | ||||||||||||||||