What is the value of value-at-risk after all?: A conditional approach using quantile regressions

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Extreme value Birnbaum-Saunders regression models applied to environmental data

Extreme value models are widely used in different areas. The Birnbaum–Saunders distribution is receiving considerable attention due to its physical arguments and its good properties. We propose a methodology based on extreme value Birnbaum–Saunders regression models, which includes model formulation, estimation, inference and checking. We further conduct a simulation study for evaluating its performance. A statistical analysis with real-world extreme value environmental data using the methodology is provided as illustration.

Prognostic Value of Pulmonary Vascular Resistance by Magnetic Resonance in Systolic Heart Failure

Abstract Background: Pulmonary hypertension is associated with poor prognosis in heart failure. However, non-invasive diagnosis is still challenging in clinical practice. Objective: We sought to assess the prognostic utility of non-invasive estimation of pulmonary vascular resistances (PVR) by cardiovascular magnetic resonance to predict adverse cardiovascular outcomes in heart failure with reduced ejection fraction (HFrEF). Methods: Prospective registry of patients with left ventricular ejection fraction (LVEF) < 40% and recently admitted for decompensated heart failure during three years. PVRwere calculated based on right ventricular ejection fraction and average velocity of the pulmonary artery estimated during cardiac magnetic resonance. Readmission for heart failure and all-cause mortality were considered as adverse events at follow-up. Results: 105 patients (average LVEF 26.0 ±7.7%, ischemic etiology 43%) were included. Patients with adverse events at long-term follow-up had higher values of PVR (6.93 ± 1.9 vs. 4.6 ± 1.7estimated Wood Units (eWu), p < 0.001). In multivariate Cox regression analysis, PVR ≥ 5 eWu(cutoff value according to ROC curve) was independently associated with increased risk of adverse events at 9 months follow-up (HR2.98; 95% CI 1.12-7.88; p < 0.03). Conclusions: In patients with HFrEF, the presence of PVR ≥ 5.0 Wu is associated with significantly worse clinical outcome at follow-up. Non-invasive estimation of PVR by cardiac magnetic resonance might be useful for risk stratification in HFrEF, irrespective of etiology, presence of late gadolinium enhancement or LVEF.

Estimation of dynamic latent variable models using simulated nonparametric moments

Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Since conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. Monte Carlo results show that the estimator performs well in comparison to other estimators that have been proposed for estimation of general DLV models.

Is the formula of Traub still up to date in antemortem blood glucose level estimation?

According to the hypothesis of Traub, also known as the 'formula of Traub', postmortem values of glucose and lactate found in the cerebrospinal fluid or vitreous humor are considered indicators of antemortem blood glucose levels. However, because the lactate concentration increases in the vitreous and cerebrospinal fluid after death, some authors postulated that using the sum value to estimate antemortem blood glucose levels could lead to an overestimation of the cases of glucose metabolic disorders with fatal outcomes, such as diabetic ketoacidosis. The aim of our study, performed on 470 consecutive forensic cases, was to ascertain the advantages of the sum value to estimate antemortem blood glucose concentrations and, consequently, to rule out fatal diabetic ketoacidosis as the cause of death. Other biochemical parameters, such as blood 3-beta-hydroxybutyrate, acetoacetate, acetone, glycated haemoglobin and urine glucose levels, were also determined. In addition, postmortem native CT scan, autopsy, histology, neuropathology and toxicology were performed to confirm diabetic ketoacidosis as the cause of death. According to our results, the sum value does not add any further information for the estimation of antemortem blood glucose concentration. The vitreous glucose concentration appears to be the most reliable marker to estimate antemortem hyperglycaemia and, along with the determination of other biochemical markers (such as blood acetone and 3-beta-hydroxybutyrate, urine glucose and glycated haemoglobin), to confirm diabetic ketoacidosis as the cause of death.

Estimation of lean meat content in pig carcasses using X-ray Computed Tomography and PLS regression

Lean meat percentage (LMP) is an important carcass quality parameter. The aim of this work is to obtain a calibration equation for the Computed Tomography (CT) scans with the Partial Least Square Regression (PLS) technique in order to predict the LMP of the carcass and the different cuts and to study and compare two different methodologies of the selection of the variables (Variable Importance for Projection — VIP- and Stepwise) to be included in the prediction equation. The error of prediction with cross-validation (RMSEPCV) of the LMP obtained with PLS and selection based on VIP value was 0.82% and for stepwise selection it was 0.83%. The prediction of the LMP scanning only the ham had a RMSEPCV of 0.97% and if the ham and the loin were scanned the RMSEPCV was 0.90%. Results indicate that for CT data both VIP and stepwise selection are good methods. Moreover the scanning of only the ham allowed us to obtain a good prediction of the LMP of the whole carcass.

Estimation of dynamic latent variable models using simulated nonparametric moments

Abstract. Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Because conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. It is shown that as the number of simulations diverges, the estimator is consistent and a higher-order expansion reveals the stochastic difference between the infeasible GMM estimator based on the same moment conditions and the simulated version. In particular, we show how to adjust standard errors to account for the simulations. Monte Carlo results show how the estimator may be applied to a range of dynamic latent variable (DLV) models, and that it performs well in comparison to several other estimators that have been proposed for DLV models.

Estimation of Genetic Divergence and Gene Flow between Culex pipiens and Culex quinquefasciatus (Diptera: Culicidae) in Argentina

Allele frequencies at seven polymorphic loci controlling the synthesis of enzymes were analyzed in six populations of Culex pipiens L. and Cx. quinquefasciatus Say. Sampling sites were situated along a north-south line of about 2,000 km in Argentina. The predominant alleles at Mdh, Idh, Gpdh and Gpi loci presented similar frequencies in all the samples. Frequencies at the Pgm locus were similar for populations pairs sharing the same geographic area. The loci Cat and Hk-1 presented significant geographic variation. The latter showed a marked latitudinal cline, with a frequency for allele b ranging from 0.99 in the northernmost point to 0.04 in the southernmost one, a pattern that may be explained by natural selection (FST = 0.46; p < 0.0001) on heat sensitive alleles. The average value of FST (0.088) and Nm (61.12) indicated a high gene flow between adjacent populations. A high correlation was found between genetic and geographic distance (r = 0.83; p < 0.001). The highest genetic identity (IN = 0.988) corresponded to the geographically closest samples from the central area. In one of these localities Cx. quinquefasciatus was predominant and hybrid individuals were detected, while in the other, almost all the specimens were identified as Cx. pipiens. To verify the fertility between Cx. pipiens and Cx. quinquefasciatus from the northern- and southernmost populations, experimental crosses were performed. Viable egg rafts were obtained from both reciprocal crosses. Hatching ranged from 76.5 to 100%. The hybrid progenies were fertile through two subsequent generations

Solvency Capital estimation and Risk Measures

This paper examines why a financial entity’s solvency capital estimation might be underestimated if the total amount required is obtained directly from a risk measurement. Using Monte Carlo simulation we show that, in some instances, a common risk measure such as Value-at-Risk is not subadditive when certain dependence structures are considered. Higher risk evaluations are obtained for independence between random variables than those obtained in the case of comonotonicity. The paper stresses, therefore, the relationship between dependence structures and capital estimation.

Bone mineral density (BMD), micro-architecture estimation (TBS) and vertebral fracture assessment (VFA) extracted from a single DXA device in combination with clinical risk factors improve significantly the identification of women at high risk of fracture

Introduction: Osteoporosis (OP) is a systemic skeletal disease characterized by a low bone mineral density (BMD) and a micro-architectural (MA) deterioration. Clinical risk factors (CRF) are often used as a MA approximation. MA is yet evaluable in daily practice by the Trabecular Bone Score (TBS) measure. TBS is a novel grey-level texture measurement reflecting bone micro-architecture based on the use of experimental variograms of 2D projection images. TBS is very simple to obtain, by reanalyzing a lumbar DXA-scan. TBS has proven to have diagnosis and prognosis value, partially independent of CRF and BMD. The aim of the OsteoLaus cohort is to combine in daily practice the CRF and the information given by DXA (BMD, TBS and vertebral fracture assessment (VFA)) to better identify women at high fracture risk. Method: The OsteoLaus cohort (1400 women 50 to 80 years living in Lausanne, Switzerland) started in 2010. This study is derived from the cohort COLAUS who started in Lausanne in 2003. The main goals of COLAUS is to obtain information on the epidemiology and genetic determinants of cardiovascular risk in 6700 men and women. CRF for OP, bone ultrasound of the heel, lumbar spine and hip BMD, VFA by DXA and MA evaluation by TBS are recorded in OsteoLaus. Preliminary results are reported. Results: We included 631 women: mean age 67.4±6.7 y, BMI 26.1±4.6, mean lumbar spine BMD 0.943±0.168 (T-score -1.4 SD), TBS 1.271±0.103. As expected, correlation between BMD and site matched TBS is low (r2=0.16). Prevalence of VFx grade 2/3, major OP Fx and all OP Fx is 8.4%, 17.0% and 26.0% respectively. Age- and BMI-adjusted ORs (per SD decrease) are 1.8 (1.2- 2.5), 1.6 (1.2-2.1), 1.3 (1.1-1.6) for BMD for the different categories of fractures and 2.0 (1.4-3.0), 1.9 (1.4-2.5), 1.4 (1.1-1.7) for TBS respectively. Only 32 to 37% of women with OP Fx have a BMD < -2.5 SD or a TBS < 1.200. If we combine a BMD < -2.5 SD or a TBS < 1.200, 54 to 60% of women with an osteoporotic Fx are identified. Conclusion: As in the already published studies, these preliminary results confirm the partial independence between BMD and TBS. More importantly, a combination of TBS subsequent to BMD increases significantly the identification of women with prevalent OP Fx which would have been miss-classified by BMD alone. For the first time we are able to have complementary information about fracture (VFA), density (BMD), micro- and macro architecture (TBS & HAS) from a simple, low ionizing radiation and cheap device: DXA. Such complementary information is very useful for the patient in the daily practice and moreover will likely have an impact on cost effectiveness analysis.

Is (1→3)-β-D-glucan the missing link from bedside assessment to pre-emptive therapy of invasive candidiasis?

ABSTRACT: Invasive candidiasis is a frequent life-threatening complication in critically ill patients. Early diagnosis followed by prompt treatment aimed at improving outcome by minimizing unnecessary antifungal use remains a major challenge in the ICU setting. Timely patient selection thus plays a key role for clinically efficient and cost-effective management. Approaches combining clinical risk factors and Candida colonization data have improved our ability to identify such patients early. While the negative predictive value of scores and predicting rules is up to 95 to 99%, the positive predictive value is much lower, ranging between 10 and 60%. Accordingly, if a positive score or rule is used to guide the start of antifungal therapy, many patients may be treated unnecessarily. Candida biomarkers display higher positive predictive values; however, they lack sensitivity and are thus not able to identify all cases of invasive candidiasis. The (1→3)-β-D-glucan (BG) assay, a panfungal antigen test, is recommended as a complementary tool for the diagnosis of invasive mycoses in high-risk hemato-oncological patients. Its role in the more heterogeneous ICU population remains to be defined. More efficient clinical selection strategies combined with performant laboratory tools are needed in order to treat the right patients at the right time by keeping costs of screening and therapy as low as possible. The new approach proposed by Posteraro and colleagues in the previous issue of Critical Care meets these requirements. A single positive BG value in medical patients admitted to the ICU with sepsis and expected to stay for more than 5 days preceded the documentation of candidemia by 1 to 3 days with an unprecedented diagnostic accuracy. Applying this one-point fungal screening on a selected subset of ICU patients with an estimated 15 to 20% risk of developing candidemia is an appealing and potentially cost-effective approach. If confirmed by multicenter investigations, and extended to surgical patients at high risk of invasive candidiasis after abdominal surgery, this Bayesian-based risk stratification approach aimed at maximizing clinical efficiency by minimizing health care resource utilization may substantially simplify the management of critically ill patients at risk of invasive candidiasis.

Usefulness of PCR-based assays to assess drug efficacy in Chagas disease chemotherapy: value and limitations

One major goal of research on Chagas disease is the development of effective chemotherapy to eliminate the infection from individuals who have not yet developed cardiac and/or digestive disease manifestations. Cure evaluation is the more complex aspect of its treatment, often leading to diverse and controversial results. The absence of reliable methods or a diagnostic gold standard to assess etiologic treatment efficacy still constitutes a major challenge. In an effort to develop more sensitive tools, polymerase chain reaction (PCR)-based assays were introduced to detect low amounts of Trypanosoma cruzi DNA in blood samples from chagasic patients, thus improving the diagnosis and follow-up evaluation after chemotherapy. In this article, I review the main problems concerning drug efficacy and criteria used for cure estimation in treated chagasic patients, and the work conducted by different groups on developing PCR methodologies to monitor treatment outcome of congenital infections as well as recent and late chronic T. cruzi infections.

Estimating Gross Value Added (GVA) across multiple scales: theoretical approach and empirical validation

This paper presents an application of the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach to the estimation of quantities of Gross Value Added (GVA) referring to economic entities defined at different scales of study. The method first estimates benchmark values of the pace of GVA generation per hour of labour across economic sectors. These values are estimated as intensive variables –e.g. €/hour– by dividing the various sectorial GVA of the country (expressed in € per year) by the hours of paid work in that same sector per year. This assessment is obtained using data referring to national statistics (top down information referring to the national level). Then, the approach uses bottom-up information (the number of hours of paid work in the various economic sectors of an economic entity –e.g. a city or a province– operating within the country) to estimate the amount of GVA produced by that entity. This estimate is obtained by multiplying the number of hours of work in each sector in the economic entity by the benchmark value of GVA generation per hour of work of that particular sector (national average). This method is applied and tested on two different socio-economic systems: (i) Catalonia (considered level n) and Barcelona (considered level n-1); and (ii) the region of Lima (considered level n) and Lima Metropolitan Area (considered level n-1). In both cases, the GVA per year of the local economic entity –Barcelona and Lima Metropolitan Area – is estimated and the resulting value is compared with GVA data provided by statistical offices. The empirical analysis seems to validate the approach, even though the case of Lima Metropolitan Area indicates a need for additional care when dealing with the estimate of GVA in primary sectors (agriculture and mining).

Estimation of the real population and its impact on the utilisation of healthcare services in Mediterranean resort regions: an ecological study.

BACKGROUND The demographic structure has a significant influence on the use of healthcare services, as does the size of the population denominators. Very few studies have been published on methods for estimating the real population such as tourist resorts. The lack of information about these problems means there is a corresponding lack of information about the behaviour of populational denominators (the floating population or tourist load) and the effect of this on the use of healthcare services. The objectives of the study were: a) To determine the Municipal Solid Waste (MSW) ratio, per person per day, among populations of known size; b) to estimate, by means of this ratio, the real population in an area where tourist numbers are very significant; and c) to determine the impact on the utilisation of hospital emergency healthcare services of the registered population, in comparison to the non-resident population, in two areas where tourist numbers are very significant. METHODS An ecological study design was employed. We analysed the Healthcare Districts of the Costa del Sol and the island of Menorca. Both are Spanish territories in the Mediterranean region. RESULTS In the two areas analysed, the correlation coefficient between the MSW ratio and admissions to hospital emergency departments exceeded 0.9, with p < 0.001. On the basis of MSW generation ratios, obtained for a control zone and also measured in neighbouring countries, we estimated the real population. For the summer months, when tourist activity is greatest and demand for emergency healthcare at hospitals is highest, this value was found to be double that of the registered population. CONCLUSION The MSW indicator, which is both ecological and indirect, can be used to estimate the real population in areas where population levels vary significantly during the year. This parameter is of interest in planning and dimensioning the provision of healthcare services.

The Strategic value of European renewable energy promotion policy

Encara falta per fer possible una transformació estratègica d'Europa del sistema d'energia, però el que és de la mateixa importància com a objectius a llarg termini de la FER i Reduccions de GEH són vinculants i forts objectius d'eficiència energètica, no només per 2020, però també per al 2030, 2040 i 2050, com aquesta força ajudaria a fixar l'augment de les energies renovables en el total d'energia consum i per reduir el total Emissions de GEH d'Europa en general, i les del sector de l'energia en particular, encara sent un dels majors emissors de gasos d'efecte hivernacle de tots els sectors. La refosa Directiva, prevista per 2011/12 ha de ser un bones finestres d'oportunitat per finalment establir objectius vinculants d'eficiència energètica, l'únic pilar que encara falta en la força energia interdependents i estratègia sobre el clima de la UE, basat en la reducció de gasos d'efecte hivernacle i i l'eficiència energètica.