Unified Bayesian Conditional Autoregressive Risk Measures using the Skew Exponential Power Distribution

Conditional Autoregressive Value-at-Risk and Conditional Autoregressive Expectile have become two popular approaches for direct measurement of market risk. Since their introduction several improvements both in the Bayesian and in the classical framework have been proposed to better account for asymmetry and local non-linearity. Here we propose a unified Bayesian Conditional Autoregressive Risk Measures approach by using the Skew Exponential Power distribution. Further, we extend the proposed models using a semiparametric P-spline approximation answering for a flexible way to consider the presence of non-linearity. To make the statistical inference we adapt the MCMC algorithm proposed in Bernardi et al. (2018) to our case. The effectiveness of the whole approach is demonstrated using real data on daily return of five stock market indices

Bayesian robust quantile regression and risk measures

Traditional Bayesian quantile regression relies on the Asymmetric Laplace distribution (ALD) due primarily to its satisfactory empirical and theoretical performances. However, the ALD displays medium tails and is not suitable for data characterized by strong deviations from the Gaussian hypothesis. In this paper, we propose an extension of the ALD Bayesian quantile regression framework to account for fat tails using the Skew Exponential Power (SEP) distribution. Besides having the τ-level quantile as a parameter, the SEP distribution has an additional key parameter governing the decay of the tails, making it attractive for robust modeling. Linear and Additive Models (AM) with penalized spline are used to show the exibility of the SEP in the Bayesian quantile regression context. Lasso priors are used in both cases to account for the problem of shrinking parameters when the parameters space becomes wide. To implement the Bayesian inference we propose a new adaptive Metropolis within Gibbs algorithm. Empirical evidence of the statistical properties of the proposed SEP Bayesian quantile regression method is provided through several examples based on both simulated and real datasets.Conditional Autoregressive Value-at-Risk (CAViaR) and Conditional Autoregressive Expectile (CARE) have become two popular approaches for direct measurement of market risk. Since their introduction in the econometric literature by the seminal papers of Engle and Manganelli (2004) and Taylor (2008), several improvements have been proposed to the original approaches allowing for different degrees of asymmetry and local non-linearity. Furthermore, Bayesian modeling of time-varying quantile and expectile regression relies on the Asymmetric Laplace (AL) distribution and the Asymmetric Gaussian (AG) distribution respectively, making impossible to consider the two risk measure in a unified framework. Here we propose two extensions of the Bayesian CAViaR and CARE class of models using the Skew Exponential Power (SEP) distribution and a flexible functional form specified by P-Spline functions. The SEP distribution includes the AL and the AG as a special cases allowing for a new general class of models, that include both CAViaR and CARE models, called Bayesian Conditional Autoregressive Risk Measures (B-CARM). Further, we consider the P-spline approximation of the models which permits to take into account for non-linearity. To estimate all the model parameters we propose a new Adaptive Independent Metropolis within Gibbs algorithm. The the effectiveness of the model is demonstrated using real data on daily return of five stock market indices

Adverse events associated with intraocular injection of anti-VEGF(bevacizumab) in retinal vein ccclusion: a case report

Introduction: Antiangiogenic agents are often administered for treatment of Branch Retinal Vein Occlusion (BRVO). Among them, Bevacizumab has noticeable antiangiogenic and antiedemigenic properties and possesses great capacity to penetrate the retinal tissue, particularly in pathological circumstances characterized by altered external or internal blood-retinal barrier.Bevacizumab has an optimal bio-efficacy based on inhibition of the activity of Vascular Endothelial Growth Factor (VEGF). Nonetheless, despite its efficacy, here we describe the adverse effects associated with intraocular injection of bevacizumab in a patient affected by retinal vein occlusion. Case presentation: We present a case report of an 11-year old Caucasian malesubject affected by BRVO in his left eye. The patient underwent an intra-vitreal (i.v.) injection of bevacizumab 100 (1.25 mg/0.05ml). After that, the patient was monitored over time through a series of analyses including Ocular Coherence Tomography, Fluorangiography, Bulbar Ultrasound, Angio MRI BCVA scores and Intra Ocular Pressure. Results: Immediately after the i.v. injection, the patient experienced a strong and relentless pain radiating from the left ocular orbit, caused by a serious and unexpected malignant glaucoma and phthisis bulbi. Furthermore, the patient did not show any sign of improvement in visual function in the follow-up and at last required an ophthalmic prosthesisas a result of a subatrophic and hypotonic eyeball. Conclusion: This case report suggests that i.v. injections of anti-VEGFs should be considered wit

Envy, Social Comparison, and Depression on Social Networking Sites: A Systematic Review

This study aims to review the evidence for the reciprocal relationship between envy and social comparison (SC) on social networking sites (SNSs) and depression. We searched PsychINFO, PubMed, and Web of Science from January 2012 to November 2022, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A total of 9 articles met our inclusion criteria. In all articles reviewed, a simple correlation was found between SC on SNSs, envy, and depression. Three cross-sectional studies successfully tested a model with envy as a mediator between SNSs and depression. The moderating role of additional variables such as self-efficacy, neuroticism, SC orientation, marital quality, and friendship type was also evident. The only two studies that were suitable to determine direction found that depression acted as a predictor rather than an outcome of SC and envy, and therefore depression might be a relevant risk factor for the negative emotional consequences of SNSs use

Pediatric tuberculosis in Italian children: Epidemiological and clinical data from the Italian register of pediatric tuberculosis

Tuberculosis (TB) is one of the leading causes of death worldwide. Over the last decades, TB has also emerged in the pediatric population. Epidemiologic data of childhood TB are still limited and there is an urgent need of more data on very large cohorts. A multicenter study was conducted in 27 pediatric hospitals, pediatric wards, and public health centers in Italy using a standardized form, covering the period of time between 1 January 2010 and 31 December 2012. Children with active TB, latent TB, and those recently exposed to TB or recently adopted/immigrated from a high TB incidence country were enrolled. Overall, 4234 children were included; 554 (13.1%) children had active TB, 594 (14.0%) latent TB and 3086 (72.9%) were uninfected. Among children with active TB, 481 (86.8%) patients had pulmonary TB. The treatment of active TB cases was known for 96.4% (n = 534) of the cases. Overall, 210 (39.3%) out of these 534 children were treated with three and 216 (40.4%) with four first-line drugs. Second-line drugs where used in 87 (16.3%) children with active TB. Drug-resistant strains of Mycobacterium tuberculosis were reported in 39 (7%) children. Improving the surveillance of childhood TB is important for public health care workers and pediatricians. A non-negligible proportion of children had drug-resistant TB and was treated with second-line drugs, most of which are off-label in the pediatric age. Future efforts should concentrate on improving active surveillance, diagnostic tools, and the availability of antitubercular pediatric formulations, also in low-endemic countries

Adherence to antibiotic treatment guidelines and outcomes in the hospitalized elderly with different types of pneumonia

Background: Few studies evaluated the clinical outcomes of Community Acquired Pneumonia (CAP), Hospital-Acquired Pneumonia (HAP) and Health Care-Associated Pneumonia (HCAP) in relation to the adherence of antibiotic treatment to the guidelines of the Infectious Diseases Society of America (IDSA) and the American Thoracic Society (ATS) in hospitalized elderly people (65 years or older). Methods: Data were obtained from REPOSI, a prospective registry held in 87 Italian internal medicine and geriatric wards. Patients with a diagnosis of pneumonia (ICD-9 480-487) or prescribed with an antibiotic for pneumonia as indication were selected. The empirical antibiotic regimen was defined to be adherent to guidelines if concordant with the treatment regimens recommended by IDSA/ATS for CAP, HAP, and HCAP. Outcomes were assessed by logistic regression models. Results: A diagnosis of pneumonia was made in 317 patients. Only 38.8% of them received an empirical antibiotic regimen that was adherent to guidelines. However, no significant association was found between adherence to guidelines and outcomes. Having HAP, older age, and higher CIRS severity index were the main factors associated with in-hospital mortality. Conclusions: The adherence to antibiotic treatment guidelines was poor, particularly for HAP and HCAP, suggesting the need for more adherence to the optimal management of antibiotics in the elderly with pneumonia

Bayesian quantile regression using the skew exponential power distribution

Traditional Bayesian quantile regression relies on the Asymmetric Laplace (AL) distribution due primarily to its satisfactory empirical and theoretical performances. However, the AL displays medium tails and it is not suitable for data characterized by strong deviations from the Gaussian hypothesis. An extension of the AL Bayesian quantile regression framework is proposed to account for fat tails using the Skew Exponential Power (SEP) distribution. Linear and Additive Models (AM) with penalized splines are considered to show the flexibility of the SEP in the Bayesian quantile regression context. Lasso priors are used in both cases to account for the problem of shrinking parameters when the parameters space becomes wide while Bayesian inference is implemented using a new adaptive Metropolis within Gibbs algorithm. Empirical evidence of the statistical properties of the proposed models is provided through several examples based on both simulated and real datasets