Optimal client recommendation for market makers in illiquid financial products

The process of liquidity provision in financial markets can result in prolonged exposure to illiquid instruments for market makers. In this case, where a proprietary position is not desired, pro-actively targeting the right client who is likely to be interested can be an effective means to offset this position, rather than relying on commensurate interest arising through natural demand. In this paper, we consider the inference of a client profile for the purpose of corporate bond recommendation, based on typical recorded information available to the market maker. Given a historical record of corporate bond transactions and bond meta-data, we use a topic-modelling analogy to develop a probabilistic technique for compiling a curated list of client recommendations for a particular bond that needs to be traded, ranked by probability of interest. We show that a model based on Latent Dirichlet Allocation offers promising performance to deliver relevant recommendations for sales traders.Comment: 12 pages, 3 figures, 1 tabl

A Compromise between Neutrino Masses and Collider Signatures in the Type-II Seesaw Model

A natural extension of the standard $SU(2)_{\rm L} \times U(1)_{\rm Y}$ gauge model to accommodate massive neutrinos is to introduce one Higgs triplet and three right-handed Majorana neutrinos, leading to a $6\times 6$ neutrino mass matrix which contains three $3\times 3$ sub-matrices $M_{\rm L}$, $M_{\rm D}$ and $M_{\rm R}$. We show that three light Majorana neutrinos (i.e., the mass eigenstates of $\nu_e$, $\nu_\mu$ and $\nu_\tau$) are exactly massless in this model, if and only if $M_{\rm L} = M_{\rm D} M_{\rm R}^{-1} M_{\rm D}^T$ exactly holds. This no-go theorem implies that small but non-vanishing neutrino masses may result from a significant but incomplete cancellation between $M_{\rm L}$ and $M_{\rm D} M_{\rm R}^{-1} M_{\rm D}^T$ terms in the Type-II seesaw formula, provided three right-handed Majorana neutrinos are of ${\cal O}(1)$ TeV and experimentally detectable at the LHC. We propose three simple Type-II seesaw scenarios with the $A_4 \times U(1)_{\rm X}$ flavor symmetry to interpret the observed neutrino mass spectrum and neutrino mixing pattern. Such a TeV-scale neutrino model can be tested in two complementary ways: (1) searching for possible collider signatures of lepton number violation induced by the right-handed Majorana neutrinos and doubly-charged Higgs particles; and (2) searching for possible consequences of unitarity violation of the $3\times 3$ neutrino mixing matrix in the future long-baseline neutrino oscillation experiments.Comment: RevTeX 19 pages, no figure

Neural Precursor-Derived Pleiotrophin Mediates Subventricular Zone Invasion by Glioma.

The lateral ventricle subventricular zone (SVZ) is a frequent and consequential site of pediatric and adult glioma spread, but the cellular and molecular mechanisms mediating this are poorly understood. We demonstrate that neural precursor cell (NPC):glioma cell communication underpins this propensity of glioma to colonize the SVZ through secretion of chemoattractant signals toward which glioma cells home. Biochemical, proteomic, and functional analyses of SVZ NPC-secreted factors revealed the neurite outgrowth-promoting factor pleiotrophin, along with required binding partners SPARC/SPARCL1 and HSP90B, as key mediators of this chemoattractant effect. Pleiotrophin expression is strongly enriched in the SVZ, and pleiotrophin knock down starkly reduced glioma invasion of the SVZ in the murine brain. Pleiotrophin, in complex with the binding partners, activated glioma Rho/ROCK signaling, and ROCK inhibition decreased invasion toward SVZ NPC-secreted factors. These findings demonstrate a pathogenic role for NPC:glioma interactions and potential therapeutic targets to limit glioma invasion. PAPERCLIP

Seasonal variations of EPG levels in gastro-intestinal parasitic infection in a southeast asian controlled locale:a statistical analysis

We present a data based statistical study on the effects of seasonal variations in the growth rates of the gastro-intestinal (GI) parasitic infection in livestock. The alluded growth rate is estimated through the variation in the number of eggs per gram (EPG) of faeces in animals. In accordance with earlier studies, our analysis too shows that rainfall is the dominant variable in determining EPG infection rates compared to other macro-parameters like temperature and humidity. Our statistical analysis clearly indicates an oscillatory dependence of EPG levels on rainfall fluctuations. Monsoon recorded the highest infection with a comparative increase of at least 2.5 times compared to the next most infected period (summer). A least square fit of the EPG versus rainfall data indicates an approach towards a super diffusive (i. e. root mean square displacement growing faster than the square root of the elapsed time as obtained for simple diffusion) infection growth pattern regime for low rainfall regimes (technically defined as zeroth level dependence) that gets remarkably augmented for large rainfall zones. Our analysis further indicates that for low fluctuations in temperature (true on the bulk data), EPG level saturates beyond a critical value of the rainfall, a threshold that is expected to indicate the onset of the nonlinear regime. The probability density functions (PDFs) of the EPG data show oscillatory behavior in the large rainfall regime (greater than 500 mm), the frequency of oscillation, once again, being determined by the ambient wetness (rainfall, and humidity). Data recorded over three pilot projects spanning three measures of rainfall and humidity bear testimony to the universality of this statistical argument. © 2013 Chattopadhyay and Bandyopadhyay

Analysis of Population Structure: A Unifying Framework and Novel Methods Based on Sparse Factor Analysis

We consider the statistical analysis of population structure using genetic data. We show how the two most widely used approaches to modeling population structure, admixture-based models and principal components analysis (PCA), can be viewed within a single unifying framework of matrix factorization. Specifically, they can both be interpreted as approximating an observed genotype matrix by a product of two lower-rank matrices, but with different constraints or prior distributions on these lower-rank matrices. This opens the door to a large range of possible approaches to analyzing population structure, by considering other constraints or priors. In this paper, we introduce one such novel approach, based on sparse factor analysis (SFA). We investigate the effects of the different types of constraint in several real and simulated data sets. We find that SFA produces similar results to admixture-based models when the samples are descended from a few well-differentiated ancestral populations and can recapitulate the results of PCA when the population structure is more “continuous,” as in isolation-by-distance models

Solitary waves in the Nonlinear Dirac Equation

In the present work, we consider the existence, stability, and dynamics of solitary waves in the nonlinear Dirac equation. We start by introducing the Soler model of self-interacting spinors, and discuss its localized waveforms in one, two, and three spatial dimensions and the equations they satisfy. We present the associated explicit solutions in one dimension and numerically obtain their analogues in higher dimensions. The stability is subsequently discussed from a theoretical perspective and then complemented with numerical computations. Finally, the dynamics of the solutions is explored and compared to its non-relativistic analogue, which is the nonlinear Schr{\"o}dinger equation. A few special topics are also explored, including the discrete variant of the nonlinear Dirac equation and its solitary wave properties, as well as the PT-symmetric variant of the model

Neuropsychiatric Events in Systemic Lupus Erythematosus: Predictors of Occurrence and Resolution in a Longitudinal Analysis of an International Inception Cohort

Objective: To determine predictors of change in neuropsychiatric (NP) event status in a large, prospective, international inception cohort of patients with systemic lupus erythematosus (SLE). // Methods: Upon enrollment and annually thereafter, NP events attributed to SLE and non-SLE causes and physician-determined resolution were documented. Factors potentially associated with the onset and resolution of NP events were determined by time-to-event analysis using a multistate modeling structure. // Results: NP events occurred in 955 (52.3%) of 1,827 patients, and 593 (31.0%) of 1,910 unique events were attributed to SLE. For SLE-associated NP (SLE NP) events, multivariate analysis revealed a positive association with male sex (P = 0.028), concurrent non-SLE NP events excluding headache (P < 0.001), active SLE (P = 0.012), and glucocorticoid use (P = 0.008). There was a negative association with Asian race (P = 0.002), postsecondary education (P = 0.001), and treatment with immunosuppressive drugs (P = 0.019) or antimalarial drugs (P = 0.056). For non-SLE NP events excluding headache, there was a positive association with concurrent SLE NP events (P < 0.001) and a negative association with African race (P = 0.012) and Asian race (P < 0.001). NP events attributed to SLE had a higher resolution rate than non-SLE NP events, with the exception of headache, which had comparable resolution rates. For SLE NP events, multivariate analysis revealed that resolution was more common in patients of Asian race (P = 0.006) and for central/focal NP events (P < 0.001). For non-SLE NP events, resolution was more common in patients of African race (P = 0.017) and less common in patients who were older at SLE diagnosis (P < 0.001). // Conclusion: In a large and long-term study of the occurrence and resolution of NP events in SLE, we identified subgroups with better and worse prognosis. The course of NP events differs greatly depending on their nature and attribution

BioPhysConnectoR: Connecting Sequence Information and Biophysical Models

<p>Abstract</p> <p>Background</p> <p>One of the most challenging aspects of biomolecular systems is the understanding of the coevolution in and among the molecule(s).</p> <p>A complete, theoretical picture of the selective advantage, and thus a functional annotation, of (co-)mutations is still lacking. Using sequence-based and information theoretical inspired methods we can identify coevolving residues in proteins without understanding the underlying biophysical properties giving rise to such coevolutionary dynamics. Detailed (atomistic) simulations are prohibitively expensive. At the same time reduced molecular models are an efficient way to determine the reduced dynamics around the native state. The combination of sequence based approaches with such reduced models is therefore a promising approach to annotate evolutionary sequence changes.</p> <p>Results</p> <p>With the <monospace>R</monospace> package <monospace>BioPhysConnectoR</monospace> we provide a framework to connect the information theoretical domain of biomolecular sequences to biophysical properties of the encoded molecules - derived from reduced molecular models. To this end we have integrated several fragmented ideas into one single package ready to be used in connection with additional statistical routines in <monospace>R</monospace>. Additionally, the package leverages the power of modern multi-core architectures to reduce turn-around times in evolutionary and biomolecular design studies. Our package is a first step to achieve the above mentioned annotation of coevolution by reduced dynamics around the native state of proteins.</p> <p>Conclusions</p> <p><monospace>BioPhysConnectoR</monospace> is implemented as an <monospace>R</monospace> package and distributed under GPL 2 license. It allows for efficient and perfectly parallelized functional annotation of coevolution found at the sequence level.</p

Association Between Severe Nonadherence to Hydroxychloroquine and Systemic Lupus Erythematosus Flares, Damage, and Mortality in 660 Patients From the SLICC Inception Cohort

OBJECTIVE: The goals of this study were to assess the associations of severe nonadherence to hydroxychloroquine (HCQ), objectively assessed by HCQ serum levels, and risks of systemic lupus erythematosus (SLE) flares, damage, and mortality rates over five years of follow-up. METHODS: The Systemic Lupus International Collaborating Clinics (SLICC) Inception Cohort is an international multicenter initiative (33 centers throughout 11 countries). The serum of patients prescribed HCQ for at least three months at enrollment were analyzed. Severe nonadherence was defined by a serum HCQ level <106 ng/mL or <53 ng/mL for HCQ doses of 400 or 200 mg/day, respectively. Associations with the risk of a flare (defined as a Systemic Lupus Erythematosus Disease Activity Index 2000 increase ≥4 points, initiation of prednisone or immunosuppressive drugs, or new renal involvement) were studied with logistic regression, and associations with damage (first SLICC/American College of Rheumatology Damage Index [SDI] increase ≥1 point) and mortality with separate Cox proportional hazard models. RESULTS: Of the 1,849 cohort participants, 660 patients (88% women) were included. Median (interquartile range) serum HCQ was 388 ng/mL (244–566); 48 patients (7.3%) had severe HCQ nonadherence. No covariates were clearly associated with severe nonadherence, which was, however, independently associated with both flare (odds ratio 3.38; 95% confidence interval [CI] 1.80–6.42) and an increase in the SDI within each of the first three years (hazard ratio [HR] 1.92 at three years; 95% CI 1.05–3.50). Eleven patients died within five years, including 3 with severe nonadherence (crude HR 5.41; 95% CI 1.43–20.39). CONCLUSION: Severe nonadherence was independently associated with the risks of an SLE flare in the following year, early damage, and five-year mortality