The Geometry of the World of Currency Volatilities

Computational Economics - Using empirical data and the properties they reveal, we develop a factor that captures changes of both currency implied correlation and volatilities. For this purpose, we...     

CAViaR-based forecast for oil price risk

As a benchmark for measuring market risk, value-at-risk (VaR) reduces the risk associated with any kind of asset to just a number (amount in terms of a currency), which can be well understood by regulators, board members, and other interested parties. This paper employs a new VaR approach due to Engle and Manganelli [Engle, R.F., Manganelli, S., 2004. CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles. Journal of Business and Economic Statistics 22, 367–381] to forecasting oil price risk. In doing so, we provide two original contributions by introducing a new exponentially weighted moving average CAViaR model and developing a mixed data regression model for multi-period VaR prediction.     

Synthesis,Surface Properties,and Self-Aggregation Behavior of a Branched N,N-Dimethylalkylamine Oxide Surfactant

Amine-oxide surfactants have emerged as highly stable, nontoxic, and cost-effective constituents of detergent formulations, specifically as wetting agents and foam boosters. With the aim of enhancing their functional behavior, a new member of this family, N,N-dimethyl-2-propylheptan-1-amine oxide, bearing a branched alkyl tail (C₁₀DAO-branched) was synthesized and purified using a simple and easily scalable strategy starting from 2-propylheptan-1-ol. 2D-nuclear magnetic resonance (NMR) and mass spectrometry confirm the obtainment of the desired product in high yield and purity. The protonation behavior of the branched surfactant is not affected by alkyl tail branching, as shown by potentiometric titrations. In contrast, surface activity and aggregation behavior of C₁₀DAO-branched is dramatically different from that of the linear analog N,N-dimethyldecyl-1-amine oxide (C₁₀DAO-linear), in that it occupies a higher area at the solution interface and aggregates at much higher concentration, forming larger aggregates, as detected using tensiometry and dynamic light scattering (DLS), respectively. Aggregation behavior of C₁₀DAO-branched is less sensitive to pH variations. Foaming tests show that C₁₀DAO-branched is a more effective foam booster than its linear analog, in both acidic and basic solutions. The experimental results indicate that the branched surfactant can be used in applications that require enhanced and pH-independent surface activity and foamability.     

Evaluation of the Molecular Landscape in PD-L1 Positive Metastatic NSCLC: Data from Campania,Italy

Background: Immune-checkpoint inhibitors (ICIs) have increased and improved the treatment options for patients with non-oncogene-addicted advanced stage non-small cell lung cancer (NSCLC). However, the role of ICIs in oncogene-addicted advanced stage NSCLC patients is still debated. In this study, in an attempt to fill in the informational gap on the effect of ICIs on other driver mutations, we set out to provide a molecular landscape of clinically relevant oncogenic drivers in programmed death-ligand 1 (PD-L1) positive NSCLC patients. Methods: We retrospectively reviewed data on 167 advanced stage NSCLC PD-L1 positive patients (≥1%) who were referred to our clinic for molecular evaluation of five driver oncogenes, namely, EGFR, KRAS, BRAF, ALK and ROS1. Results: Interestingly, n = 93 (55.7%) patients showed at least one genomic alteration within the tested genes. Furthermore, analyzing a subset of patients with PD-L1 tumor proportion score (TPS) ≥ 50% and concomitant gene alterations (n = 8), we found that n = 3 (37.5%) of these patients feature clinical benefit with ICIs administration, despite the presence of a concomitant KRAS gene alteration. Conclusions: In this study, we provide a molecular landscape of clinically relevant biomarkers in NSCLC PD-L1 positive patients, along with data evidencing the clinical benefit of ICIs in patient NSCLC PD-L1 positive alterations.     

生产饮料工业用瓶盖的特种注塑机

Ferromatik Milacron公司新近推出的特种注塑机Cap-Tec,为各种瓶、纸盒包装容器、立式袋的塑料密封提供了经济的生产方法。     

The Molecular Landscape of Primary Acral Melanoma: A Multicenter Study of the Italian Melanoma Intergroup (IMI)

Acral melanoma (AM) is a rare and aggressive subtype of melanoma affecting the palms, soles, and nail apparatus with similar incidence among different ethnicities. AM is unrelated to ultraviolet radiation and has a low mutation burden but frequent chromosomal rearrangements and gene amplifications. Next generation sequencing of 33 genes and somatic copy number variation (CNV) analysis with genome-wide single nucleotide polymorphism arrays were performed in order to molecularly characterize 48 primary AMs of Italian patients in association with clinicopathological and prognostic features. BRAF was the most commonly mutated gene, followed by NRAS and TP53, whereas TERT promoter, KIT, and ARID1A were less frequently mutated. Gains and losses were recurrently found in the 1q, 6p, 7, 8q, 20 and 22 chromosomes involving PREX2, RAC1, KMT2C, BRAF, CCND1, TERT, and AKT3 genes, and in the 6q, 9, 10, 11q and 16q chromosomes including CDKN2A, PTEN, and ADAMTS18 genes, respectively. This study confirmed the variety of gene mutations and the high load of CNV in primary AM. Some genomic alterations were associated with histologic prognostic features. BRAF mutations, found with a higher rate than previously reported, correlated with a low Breslow thickness, low mitotic count, low CNV of the AMs, and with early-stage of disease.     

Calibrating the Italian Smile with Time-Varying Volatility and Heavy-Tailed Models

In this paper, we consider several time-varying volatility and/or heavy-tailed models to explain the dynamics of return time series and to fit the volatility smile for exchange-traded options where the underlying is the main Italian stock index. Given observed prices for the time period we investigate, we calibrate both continuous-time and discrete-time models. First, we estimate the models from a time-series perspective (i.e. under the historical probability measure) by investigating more than 10 years of daily index price log-returns. Then, we explore the risk-neutral measure by fitting the values of the implied volatility for numerous strikes and maturities during the highly volatile period from April 1, 2007 (prior to the subprime mortgage crisis in the US) to March 30, 2012. We assess the extent to which time-varying volatility and heavy-tailed distributions are needed to explain the behavior of the most important stock index of the Italian market.