The credit risk(+) model with general sector correlations

We consider an enhancement of the credit risk+ model to incorporate correlations between sectors. We model the sector default rates as linear combinations of a common set of independent variables that represent macro-economic variables or risk factors. We also derive the formula for exact VaR contributions at the obligor level.

Risk Minimizing Option Pricing in a Semi-Markov Modulated Market

We address risk minimizing option pricing in a semi-Markov modulated market where the floating interest rate depends on a finite state semi-Markov process. The growth rate and the volatility of the stock also depend on the semi-Markov process. Using the Föllmer–Schweizer decomposition we find the locally risk minimizing price for European options and the corresponding hedging strategy. We develop suitable numerical methods for computing option prices.

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.

A Haplotype at the UCP1 Gene Locus Contributes to Genetic Risk for Type 2 Diabetes in Asian Indians (CURES-72)

Background: The gene encoding for uncoupling protein-1 (UCP1) is considered to be a candidate gene for type 2 diabetes because of its role in thermogenesis and energy expenditure. The objective of the study was to examine whether genetic variations in the UCP1 gene are associated with type 2 diabetes and its related traits in Asian Indians. Methods: The study subjects, 810 type 2 diabetic subjects and 990 normal glucose tolerant (NGT) subjects, were chosen from the Chennai Urban Rural Epidemiological Study (CURES), an ongoing population-based study in southern India. The polymorphisms were genotyped using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Linkage disequilibrium (LD) was estimated from the estimates of haplotypic frequencies. Results: The three polymorphisms, namely -3826A -> G, an A -> C transition in the 5'-untranslated region (UTR) and Met229Leu, were not associated with type 2 diabetes. However, the frequency of the A-C-Met (-3826A -> G-5'UTR A -> C-Met229Leu) haplotype was significantly higher among the type 2 diabetic subjects (2.67%) compared with the NGT subjects (1.45%, P < 0.01). The odds ratio for type 2 diabetes for the individuals carrying the haplotype A-C-Met was 1.82 (95% confidence interval, 1.29-2.78, P = 0.009). Conclusions: The haplotype, A-C-Met, in the UCP1 gene is significantly associated with the increased genetic risk for developing type 2 diabetes in Asian Indians.

Methylenetetrahydrofolate reductase gene polymorphisms and risk of acute lymphoblastic leukemia in children

Methylenetetrahydrofolate reductase (MTHFR) is a critical enzyme in folate metabolism and is involved in DNA synthesis, DNA repair and DNA methylation. Genetic polymorphisms of this enzyme have been shown to impact several diseases, including cancer. Leukemias are malignancies arising from rapidly proliferating hematopoietic cells having great requirement of DNA synthesis. This case-control study was undertaken to analyze the association of the MTHFR gene polymorphisms 677 C"T and 1298 A"C and the risk of acute lymphoblastic leukemia in children. Materials and Methods: Eighty-six patients aged below 15 years with a confirmed diagnosis of acute lymphoblastic leukemia (ALL) and 99 matched controls were taken for this study. Analysis of the polymorphisms was done using the polymerase chain reaction -restriction fragment length polymorphism (PCR-RFLP) method. Results: Frequency of MTHFR 677 CC and CT were 85.9% and 14.1% in the controls, and 84.9% and 15.1% in the cases. The 'T' allele frequency was 7% and 7.5% in cases and controls respectively. The frequency of MTHFR 1298 AA, AC, and CC were 28.3%, 55.6% and 16.1% for controls and 23.3%, 59.3% and 17.4% for cases respectively. The 'C' allele frequency for 1298 A→C was 43.9% and 47% respectively for controls and cases. The odds ratio (OR) for C677T was 1.08 (95% CI 0.48- 2.45, p = 0.851) and OR for A1298C was 1.29(95% CI 0.65-2.29, p = 0.46) and OR for 1298 CC was 1.31 (95% CI 0.53-3.26, p =0.56). The OR for the combined heterozygous status (677 CT and 1298 AC) was 1.94 (95% CI 0.58 -6.52, p = 0.286). Conclusion: The prevalence of 'T' allele for 677 MTHFR polymorphism was low in the population studied. There was no association between MTHFR 677 C→T and 1298 A→C gene polymorphisms and risk of ALL, which may be due to the small sample size.