Dynamic asset (and liability) management under market and credit risk

We introduce a modelling paradigm which integrates credit risk and market risk in describing the random dynamical behaviour of the underlying fixed income assets. We then consider an asset and liability management (ALM) problem and develop a mul- tistage stochastic programming model which focuses on optimum risk decisions. These models exploit the dynamical multiperiod structure of credit risk and provide insight into the corrective recourse decisions whereby issues such as the timing risk of default is appropriately taken into consideration. We also present a index tracking model in which risk is measured (and optimised) by the CVaR of the tracking portfolio in relation to the index. Both in- and out-of-sample (backtesting) experiments are undertaken to validate our approach. In this way we are able to demonstrate the feasibility and flexibility of the chosen framework

Moody's Correlated Binomial Default Distributions for Inhomogeneous Portfolios

This paper generalizes Moody's correlated binomial default distribution for homogeneous (exchangeable) credit portfolio, which is introduced by Witt, to the case of inhomogeneous portfolios. As inhomogeneous portfolios, we consider two cases. In the first case, we treat a portfolio whose assets have uniform default correlation and non-uniform default probabilities. We obtain the default probability distribution and study the effect of the inhomogeneity on it. The second case corresponds to a portfolio with inhomogeneous default correlation. Assets are categorized in several different sectors and the inter-sector and intra-sector correlations are not the same. We construct the joint default probabilities and obtain the default probability distribution. We show that as the number of assets in each sector decreases, inter-sector correlation becomes more important than intra-sector correlation. We study the maximum values of the inter-sector default correlation. Our generalization method can be applied to any correlated binomial default distribution model which has explicit relations to the conditional default probabilities or conditional default correlations, e.g. Credit Risk${}^{+}$, implied default distributions. We also compare some popular CDO pricing models from the viewpoint of the range of the implied tranche correlation.Comment: 29 pages, 17 figures and 1 tabl

Correlation Structures of Correlated Binomial Models and Implied Default Distribution

We show how to analyze and interpret the correlation structures, the conditional expectation values and correlation coefficients of exchangeable Bernoulli random variables. We study implied default distributions for the iTraxx-CJ tranches and some popular probabilistic models, including the Gaussian copula model, Beta binomial distribution model and long-range Ising model. We interpret the differences in their profiles in terms of the correlation structures. The implied default distribution has singular correlation structures, reflecting the credit market implications. We point out two possible origins of the singular behavior.Comment: 16 pages, 7 figure

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

We introduce the \texttt{pyunicorn} (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. \texttt{pyunicorn} is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics or network surrogates. Additionally, \texttt{pyunicorn} provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis (RQA), recurrence networks, visibility graphs and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.Comment: 28 pages, 17 figure

Portfolio selection problems in practice: a comparison between linear and quadratic optimization models

Several portfolio selection models take into account practical limitations on the number of assets to include and on their weights in the portfolio. We present here a study of the Limited Asset Markowitz (LAM), of the Limited Asset Mean Absolute Deviation (LAMAD) and of the Limited Asset Conditional Value-at-Risk (LACVaR) models, where the assets are limited with the introduction of quantity and cardinality constraints. We propose a completely new approach for solving the LAM model, based on reformulation as a Standard Quadratic Program and on some recent theoretical results. With this approach we obtain optimal solutions both for some well-known financial data sets used by several other authors, and for some unsolved large size portfolio problems. We also test our method on five new data sets involving real-world capital market indices from major stock markets. Our computational experience shows that, rather unexpectedly, it is easier to solve the quadratic LAM model with our algorithm, than to solve the linear LACVaR and LAMAD models with CPLEX, one of the best commercial codes for mixed integer linear programming (MILP) problems. Finally, on the new data sets we have also compared, using out-of-sample analysis, the performance of the portfolios obtained by the Limited Asset models with the performance provided by the unconstrained models and with that of the official capital market indices

Toxic Epidermal Necrolysis after Pemetrexed and Cisplatin for Non-Small Cell Lung Cancer in a Patient with Sharp Syndrome

Background: Pemetrexed is an antifolate drug approved for maintenance and second-line therapy, and, in combination with cisplatin, for first-line treatment of advanced nonsquamous non-small cell lung cancer. The side-effect profile includes fatigue, hematological and gastrointestinal toxicity, an increase in hepatic enzymes, sensory neuropathy, and pulmonary and cutaneous toxicity in various degrees. Case Report: We present the case of a 58-year-old woman with history of Sharp's syndrome and adenocarcinoma of the lung, who developed toxic epidermal necrolysis after the first cycle of pemetrexed, including erythema, bullae, extensive skin denudation, subsequent systemic inflammation and severe deterioration in general condition. The generalized skin lesions occurred primarily in the previous radiation field and responded to immunosuppressive treatment with prednisone. Conclusion: Although skin toxicity is a well-known side effect of pemetrexed, severe skin reactions after pemetrexed administration are rare. Caution should be applied in cases in which pemetrexed is given subsequent to radiation therapy, especially in patients with pre-existing skin diseases

Appropriate Inhibition of Orexigenic Hypothalamic Arcuate Nucleus Neurons Independently of Leptin Receptor/STAT3 Signaling

Leptin directly suppresses the activity of orexigenic neurons in the hypothalamic arcuate nucleus (ARC). We examined c-Fos-like immunoreactivity (CFLIR) as a marker of ARC neuronal activity in db/db mice devoid of the signaling form of the leptin receptor (LRb) and s/s mice that express LRbS1138 [which is defective for STAT3 (signal transducer and activator of transcription) signaling]. Both db/db and s/s animals are hyperphagic and obese. This analysis revealed that CFLIR in agouti related peptide-expressing orexigenic ARC neurons is basally elevated in db/db but not s/s mice. Consistent with these observations, electrophysiologic evaluation of a small number of neurons in s/s animals suggested that leptin appropriately suppresses the frequency of IPSCs on ARC proopiomelanocortin (POMC) neurons that are mediated by the release of GABA from orexigenic ARC neurons. CFLIR in POMC neurons of s/s mice was also increased compared with db/db animals. Thus, these data suggest that, although LRb→STAT3 signaling is crucial for the regulation of feeding, it is not required for the acute or chronic regulation of orexigenic ARC neurons, and the activation of STAT3-mediated transcription by leptin is not required for the appropriate development of leptin responsiveness in these neurons

Mutational Analysis of the SOX9 Gene in Campomelic Dysplasia and Autosomal Sex Reversal: Lack of Genotype/Phenotype Correlations

It has previously been shown that, in the heterozygous state, mutations in the SOX9 gene cause campomelic dysplasia (CD) and the often associated autosomal XY sex reversal. In 12 CD patients, 10 novel mutations and one recurrent mutation were characterized in one SOX9 allele each, and in one case, no mutation was found. Four missense mutations are all located within the high mobility group (HMG) domain. They either reduce or abolish the DNA-binding ability of the mutant SOX9 proteins. Among the five nonsense and three frameshift mutations identified, two leave the C-terminal transactivation (TA) domain encompassing residues 402-509 of SOX9 partly or almost completely intact. When tested in cell transfection experiments, the recurrent nonsense mutation Y440X, found in two patients who survived for four and more than 9 years, respectively, exhibits some residual transactivation ability. In contrast, a frameshift mutation extending the protein by 70 residues at codon 507, found in a patient who died shortly after birth, showed no transactivation. This is apparently due to instability of the mutant SOX9 protein as demonstrated by Western blotting. Amino acid substitutions and nonsense mutations are found in patients with and without XY sex reversal, indicating that sex reversal in CD is subject to variable penetrance. Finally, none of 18 female patients with XY gonadal dysgenesis (Swyer syndrome) showed an altered SOX9 banding pattern in SSCP assays, providing evidence that SOX9 mutations do not usually result in XY sex reversal without skeletal malformation

The Detrimental Effects of Oxytocin-Induced Conformity on Dishonesty in Competition

Justifications may promote unethical behavior because they constitute a convenient loophole through which people can gain from immoral behavior and preserve a positive self-image at the same time. A justification that is widely used is rooted in conformity: Unethical choices become more permissible because one's peers are expected to make the same unethical choices. In the current study, we tested whether an exogenous alteration of conformity led to a lower inclination to adhere to a widely accepted norm (i.e., honesty) under the pressure of competition. We took advantage of the well-known effects of intranasally applied oxytocin on affiliation, in-group conformity, and in-group favoritism in humans. We found that conformity was enhanced by oxytocin, and this enhancement had a detrimental effect on honesty in a competitive environment but not in a noncompetitive environment. Our findings contribute to recent evidence showing that competition may lead to unethical behavior and erode moral values

Whole Exome Sequencing of Patients with Steroid-Resistant Nephrotic Syndrome

BACKGROUND AND OBJECTIVES: Steroid-resistant nephrotic syndrome overwhelmingly progresses to ESRD. More than 30 monogenic genes have been identified to cause steroid-resistant nephrotic syndrome. We previously detected causative mutations using targeted panel sequencing in 30% of patients with steroid-resistant nephrotic syndrome. Panel sequencing has a number of limitations when compared with whole exome sequencing. We employed whole exome sequencing to detect monogenic causes of steroid-resistant nephrotic syndrome in an international cohort of 300 families. DESIGN, SETTING, PARTIIPANTS AND MEASUREMENTS: Three hundred thirty-five individuals with steroid-resistant nephrotic syndrome from 300 families were recruited from April of 1998 to June of 2016. Age of onset was restricted to <25 years of age. Exome data were evaluated for 33 known monogenic steroid-resistant nephrotic syndrome genes. RESULTS: In 74 of 300 families (25%), we identified a causative mutation in one of 20 genes known to cause steroid-resistant nephrotic syndrome. In 11 families (3.7%), we detected a mutation in a gene that causes a phenocopy of steroid-resistant nephrotic syndrome. This is consistent with our previously published identification of mutations using a panel approach. We detected a causative mutation in a known steroid-resistant nephrotic syndrome gene in 38% of consanguineous families and in 13% of nonconsanguineous families, and 48% of children with congenital nephrotic syndrome. A total of 68 different mutations were detected in 20 of 33 steroid-resistant nephrotic syndrome genes. Fifteen of these mutations were novel. NPHS1, PLCE1, NPHS2, and SMARCAL1 were the most common genes in which we detected a mutation. In another 28% of families, we detected mutations in one or more candidate genes for steroid-resistant nephrotic syndrome. CONCLUSIONS: Whole exome sequencing is a sensitive approach toward diagnosis of monogenic causes of steroid-resistant nephrotic syndrome. A molecular genetic diagnosis of steroid-resistant nephrotic syndrome may have important consequences for the management of treatment and kidney transplantation in steroid-resistant nephrotic syndrome