Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range

Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even more important, especially during the 2008-09 global financial crisis. We propose some novel nonlinear threshold conditional autoregressive VaR (CAViaR) models that incorporate intra-day price ranges. Model estimation and inference are performed using the Bayesian approach via the link with the Skewed-Laplace distribution. We examine how a range of risk models perform during the 2008-09 financial crisis, and evaluate how the crisis affects the performance of risk models via forecasting VaR. Empirical analysis is conducted on five Asia-Pacific Economic Cooperation stock market indices as well as two exchange rate series. We examine violation rates, back-testing criteria, market risk charges and quantile loss function values to measure and assess the forecasting performance of a variety of risk models. The proposed threshold CAViaR model, incorporating range information, is shown to forecast VaR more efficiently than other models, across the series considered, which should be useful for financial practitioners.Value-at-Risk; CAViaR model; Skewed-Laplace distribution; intra-day range; backtesting; Markov chain Monte Carlo

Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range

Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even more important, especially during the 2008-09 global financial crisis. We pro- pose some novel nonlinear threshold conditional autoregressive VaR (CAViaR) models that incorporate intra-day price ranges. Model estimation and inference are performed using the Bayesian approach via the link with the Skewed-Laplace distribution. We examine how a range of risk models perform during the 2008-09 financial crisis, and evaluate how the crisis aects the performance of risk models via forecasting VaR. Empirical analysis is conducted on five Asia-Pacific Economic Cooperation stock market indices as well as two exchange rate series. We examine violation rates, back-testing criteria, market risk charges and quantile loss function values to measure and assess the forecasting performance of a variety of risk models. The proposed threshold CAViaR model, incorporating range information, is shown to forecast VaR more eficiently than other models, across the series considered, which should be useful for financial practitioners.Value-at-Risk; CAViaR model; Skewed-Laplace distribution; intra-day range; backtesting, Markov chain Monte Carlo.

Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range

Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even more important, especially during the 2008-09 global financial crisis. We pro- pose some novel nonlinear threshold conditional autoregressive VaR (CAViaR) models that incorporate intra-day price ranges. Model estimation and inference are performed using the Bayesian approach via the link with the Skewed-Laplace distribution. We examine how a range of risk models perform during the 2008-09 financial crisis, and evaluate how the crisis affects the performance of risk models via forecasting VaR. Empirical analysis is conducted on five Asia-Pacific Economic Cooperation stock market indices as well as two exchange rate series. We examine violation rates, back-testing criteria, market risk charges and quantile loss function values to measure and assess the forecasting performance of a variety of risk models. The proposed threshold CAViaR model, incorporating range information, is shown to forecast VaR more efficiently than other models, across the series considered, which should be useful for financial practitioners.Value-at-Risk; CAViaR model; Skewed-Laplace distribution; intra-day range; backtesting, Markov chain Monte Carlo.

A new twist to preheating

Metric perturbations typically strengthen field resonances during preheating. In contrast we present a model in which the super-Hubble field resonances are completely {\em suppressed} when metric perturbations are included. The model is the nonminimal Fakir-Unruh scenario which is exactly solvable in the long-wavelength limit when metric perturbations are included, but exhibits exponential growth of super-Hubble modes in their absence. This gravitationally enhanced integrability is exceptional, both for its rarity and for the power with which it illustrates the importance of including metric perturbations in consistent studies of preheating. We conjecture a no-go result - there exists no {\em single-field} model with growth of cosmologically-relevant metric perturbations during preheating.Comment: 6 pages, 3 figures, Version to appear in Physical Review

Pharmaceutical Effects of Inhibiting the Soluble Epoxide Hydrolase in Canine Osteoarthritis

Osteoarthritis (OA) is a degenerative joint disease that causes pain and bone deterioration driven by an increase in prostaglandins (PGs) and inflammatory cytokines. Current treatments focus on inhibiting prostaglandin production, a pro-inflammatory lipid metabolite, with NSAID drugs; however, other lipid signaling targets could provide safer and more effective treatment strategies. Epoxides of polyunsaturated fatty acids (PUFAs) are anti-inflammatory lipid mediators that are rapidly metabolized by the soluble epoxide hydrolase (sEH) into corresponding vicinal diols. Interestingly, diol levels are increased in the synovial fluid of humans with OA, warranting further research on the biological role of this lipid pathway in the progression of OA. sEH inhibitors (sEHI) stabilize these biologically active, anti-inflammatory lipid epoxides, resulting in analgesia in both neuropathic, and inflammatory pain conditions. Most experimental studies testing the analgesic effects of sEH inhibitors have used experimental rodent models, which do not completely represent the complex etiology of painful diseases. Here, we tested the efficacy of sEHI in aged dogs with natural arthritis to provide a better representation of the clinical manifestations of pain. Two sEHI were administered orally, once daily for 5 days to dogs with naturally occurring arthritis to assess efficacy and pharmacokinetics. Blinded technicians recorded the behavior of the arthritic dogs based on pre-determined criteria to assess pain and function. After 5 days, EC1728 significantly reduced pain at a dose of 5 mg/kg compared to vehicle controls. Pharmacokinetic evaluation showed concentrations exceeding the enzyme potency in both plasma and synovial fluid. In vitro data showed that epoxyeicosatrienoic acid (EETs), epoxide metabolites of arachidonic acid, decreased inflammatory cytokines, IL-6 and TNF-α, and reduced cytotoxicity in canine chondrocytes challenged with IL1β to simulate an arthritic environment. These results provide the first example of altering lipid epoxides as a therapeutic target for OA potentially acting by protecting chondrocytes from inflammatory induced cytotoxicity. Considering the challenges and high variability of naturally occurring disease in aged dogs, these data provide initial proof of concept justification that inhibiting the sEH is a non-NSAID, non-opioid, disease altering strategy for treating OA, and warrants further investigation

Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers

Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]-positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2 x 10(53)). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2 x 10(-20)). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management

Dry-air-stable lithium silicide-lithium oxide core-shell nanoparticles as high-capacity prelithiation reagents

Rapid progress has been made in realizing battery electrode materials with high capacity and long-term cyclability in the past decade. However, low first-cycle Coulombic efficiency as a result of the formation of a solid electrolyte interphase and Li trapping at the anodes, remains unresolved. Here we report LixSi-Li2O core-shell nanoparticles as an excellent prelithiation reagent with high specific capacity to compensate the first-cycle capacity loss. These nanoparticles are produced via a one-step thermal alloying process. LixSi-Li2O core-shell nanoparticles are processible in a slurry and exhibit high capacity under dry-air conditions with the protection of a Li2O passivation shell, indicating that these nanoparticles are potentially compatible with industrial battery fabrication processes. Both Si and graphite anodes are successfully prelithiated with these nanoparticles to achieve high first-cycle Coulombic efficiencies of 94% to 4100%. The LixSi-Li2O core-shell nanoparticles enable the practical implementation of high-performance electrode materials in lithium-ion batteries.open6

A “Coiled-Coil” Motif Is Important for Oligomerization and DNA Binding Properties of Human Cytomegalovirus Protein UL77

Human cytomegalovirus (HCMV) UL77 gene encodes the essential protein UL77, its function is characterized in the present study. Immunoprecipitation identified monomeric and oligomeric pUL77 in HCMV infected cells. Immunostaining of purified virions and subviral fractions showed that pUL77 is a structural protein associated with capsids. In silico analysis revealed the presence of a coiled-coil motif (CCM) at the N-terminus of pUL77. Chemical cross-linking of either wild-type pUL77 or CCM deletion mutant (pUL77ΔCCM) implicated that CCM is critical for oligomerization of pUL77. Furthermore, co-immunoprecipitations of infected and transfected cells demonstrated that pUL77 interacts with the capsid-associated DNA packaging motor components, pUL56 and pUL104, as well as the major capsid protein. The ability of pUL77 to bind dsDNA was shown by an in vitro assay. Binding to certain DNA was further confirmed by an assay using biotinylated 36-, 250-, 500-, 1000-meric dsDNA and 966-meric HCMV-specific dsDNA designed for this study. The binding efficiency (BE) was determined by image processing program defining values above 1.0 as positive. While the BE of the pUL56 binding to the 36-mer bio-pac1 containing a packaging signal was 10.0±0.63, the one for pUL77 was only 0.2±0.03. In contrast to this observation the BE of pUL77 binding to bio-500 bp or bio-1000 bp was 2.2±0.41 and 4.9±0.71, respectively. By using pUL77ΔCCM it was demonstrated that this protein could not bind to dsDNA. These data indicated that pUL77 (i) could form homodimers, (ii) CCM of pUL77 is crucial for oligomerization and (iii) could bind to dsDNA in a sequence independent manner

Chronic Methamphetamine Administration Causes Differential Regulation of Transcription Factors in the Rat Midbrain

Methamphetamine (METH) is an addictive and neurotoxic psychostimulant widely abused in the USA and throughout the world. When administered in large doses, METH can cause depletion of striatal dopamine terminals, with preservation of midbrain dopaminergic neurons. Because alterations in the expression of transcription factors that regulate the development of dopaminergic neurons might be involved in protecting these neurons after toxic insults, we tested the possibility that their expression might be affected by toxic doses of METH in the adult brain. Male Sprague-Dawley rats pretreated with saline or increasing doses of METH were challenged with toxic doses of the drug and euthanized two weeks later. Animals that received toxic METH challenges showed decreases in dopamine levels and reductions in tyrosine hydroxylase protein concentration in the striatum. METH pretreatment protected against loss of striatal dopamine and tyrosine hydroxylase. In contrast, METH challenges caused decreases in dopamine transporters in both saline- and METH-pretreated animals. Interestingly, METH challenges elicited increases in dopamine transporter mRNA levels in the midbrain in the presence but not in the absence of METH pretreatment. Moreover, toxic METH doses caused decreases in the expression of the dopamine developmental factors, Shh, Lmx1b, and Nurr1, but not in the levels of Otx2 and Pitx3, in saline-pretreated rats. METH pretreatment followed by METH challenges also decreased Nurr1 but increased Otx2 and Pitx3 expression in the midbrain. These findings suggest that, in adult animals, toxic doses of METH can differentially influence the expression of transcription factors involved in the developmental regulation of dopamine neurons. The combined increases in Otx2 and Pitx3 expression after METH preconditioning might represent, in part, some of the mechanisms that served to protect against METH-induced striatal dopamine depletion observed after METH preconditioning

Correlation-consistency cartography of the double-inflation landscape

We show explicitly some exciting features of double inflation: (i) it can often lead to strongly correlated adiabatic and entropy (isocurvature) power spectra; (ii) the two-field slow-roll consistency relations can be violated when the correlation is large at the Hubble crossing; (iii) the spectra of adiabatic and entropy perturbations can be strongly scale dependent and tilted toward either the red or blue. These effects are typically due to a light or time-dependent entropy mass and a non-negligible angular velocity in field space during inflation. They are illustrated via a multiparameter numerical search for correlations in two concrete models. The correlation is found to be particularly strong in a supersymmetric scenario due to the rapid growth of entropy perturbations in the tachyonic region separating the two inflationary stages. Our analysis suggests that realistic double-inflation models will provide a rich and fruitful arena for the application of future cosmic data sets and new approximation schemes which go beyond slow roll