抛物型模糊二叉树欧式期权定价模型

利用可信性理论对抛物型模糊二叉树期权定价模型进行了研究,推导出单期二叉树模型欧式期权价值的期望值,拓展了上升因子为三角模糊变量的单期二叉树欧式期权定价模型.而抛物型模糊数能够更好地捕捉股价变化过程中的不确定性,使模型的适用范围更广.     

Sarmanov family of multivariate distributions for bivariate dynamic claim counts model

To predict future claims, it is well-known that the most recent claims are more predictive than older ones. However, classic panel data models for claim counts, such as the multivariate negative binomial distribution, do not put any time weight on past claims. More complex models can be used to consider this property, but often need numerical procedures to estimate parameters. When we want to add a dependence between different claim count types, the task would be even more difficult to handle. In this paper, we propose a bivariate dynamic model for claim counts, where past claims experience of a given claim type is used to better predict the other type of claims. This new bivariate dynamic distribution for claim counts is based on random effects that come from the Sarmanov family of multivariate distributions. To obtain a proper dynamic distribution based on this kind of bivariate priors, an approximation of the posterior distribution of the random effects is proposed. The resulting model can be seen as an extension of the dynamic heterogeneity model described in Bolancé et al. (2007). We apply this model to two samples of data from a major Canadian insurance company, where we show that the proposed model is one of the best models to adjust the data. We also show that the proposed model allows more flexibility in computing predictive premiums because closed-form expressions can be easily derived for the predictive distribution, the moments and the predictive moments.     

Optimality conditions for vector equilibrium problems in normed spaces

By using the concepts of contingent epiderivative, radial epiderivative, Clarke tangent epiderivative and Y-epiderivative, we present necessary and sufficient conditions for the weakly efficient solution, the Henig efficient solution, and the globally proper efficient solution, respectively, to vector equilibrium problems with constraints.     

具有不同借贷利率的BlackScholes模型

在不同借贷利率以及股票的期望收益率、波动率和红利率都随时间变化（非随机）情形下,利用倒向随机微分方程及Ｆｅｙｎｍ ａｎＫａｃ公式得到欧式看涨和看跌期权定价公式．由此可看出借贷利率各自对期权价格的影响,并得到欧式看涨和看跌期权的平价关系．     

负二项回归模型的推广及其在分类费率厘定中的应用

分类费率厘定中最常使用的模型之一是泊松回归模型,但当损失次数数据存在过离散特征时,通常会采用负二项回归模型。本文将两参数的负二项回归模型推广到了三参数情况,并用它来解决分类费率厘定中的过离散(over-dispersion)问题。本文通过对一组汽车保险损失数据的拟合表明,三参数的负二项分布回归模型可以有效改善对实际损失数据的拟合效果。     

Analysis,levels and seasonal variation of cyanotoxins in freshwater ecosystems

Nutrient over-enrichment in freshwater environments, together with the on-going climate change, favour the toxin-producing cyanobacteria bloom. Human health hazard may arise from drinking contaminated water. Additionally, cyanobacterial blooms affect other economic areas such as tourism, recreation, commercial fishery, water management and monitoring. Nowadays there is a scarcity of information on seasonal variations of cyanotoxins in various regions. Understanding of historical trends and seasonal variation patters is a foundation for forecasting and will help to develop effective water management strategies.This review gives an overview of cyanotoxins' analysis and levels in freshwater environments with particular emphasis on seasonal variations in Europe. Recent analytical approaches are discussed and the seasonal patterns for three major European climate zones (Mediterranean, continental, and Atlantic) were distinguished. Additionally, data from multi-year studies showed a tendency of increasing cyanotoxins' levels.     

Analysis of 32 priority substances from EU water framework directive in wastewaters,surface and drinking waters with a fast sample treatment methodology

A simple, fast, and sensitive method is proposed for the analysis of 32 priority substances (PS) from EU Water Framework Directive (WFD) and the first Watch List in effluents of wastewater treatment plants (EWW), surface waters (SW) and drinking waters (DW). Dispersive liquid-liquid microextraction (DLLME) and gas chromatography coupled to tandem mass spectrometry (GC-MS/MS) is used. For DLLME, a mixture of 1,1,2-trichloroethane as extraction solvent (75 µL) and acetonitrile as disperser solvent (3.2 mL) is proposed. The method was validated in EWW, SW and DW, showing satisfactory accuracy values ranging from 90% to 104%, good precision (relative standard deviation, RSD%, lower than 13%) and uncertainty values between 7% and 34%. Regarding sensitivity, method limits of quantification (MLOQs) of 4.8, 5.2 and 8.8 ng L^?1 for DW, SW and EWW, respectively, were obtained. The developed method was applied to analyze PS in water from effluents of waste water treatment plants (WWTPs), surface water of the Llobregat River and its main tributaries (Catalonia, NE Spain) and drinking water from a Drinking Water Treatment Plant (DWTP). Moreover, the efficiency of treatment plants (DWTP, WWTP) on the elimination of PS was evaluated. Only 3 PS (lindane, terbutryn and dicofol) were detected, being terbutryn the compound found at the highest levels (up to 493 ng L^?1 in EWW samples). Regarding environmental quality standard (WFD) for terbutryn in surface waters, only one sample, the Rubí stream (431 ng L^?1), showed levels of terbutryn higher than maximum allowable concentration (340 ng L^?1).     

Recent studies on advance spectroscopic techniques for the identification of microorganisms: A review

The continuous development of resistance to antibiotic drugs by microorganisms causes high mortality and morbidity. Pathogens with distinct features and biochemical abilities make them destructive to human health. Therefore, early identification of the pathogen is of substantial importance for quick ailments and healthcare outcomes. Several phenotype methods are used for the identification and resistance determination but most of the conventional procedures are time-consuming, costly, and give qualitative results. Recently, great focus has been made on the utilization of advanced techniques for microbial identification. This review is focused on the research studies performed in the last five years for the identification of microorganisms particularly, bacteria using advanced spectroscopic techniques including mass spectrometry (MS), infrared (IR) spectroscopy, Raman spectroscopy (RS), and nuclear magnetic resonance (NMR) spectroscopy. Among all the techniques, MS techniques, particularly MALDI-TOF/MS have been widely utilized for microbial identification. A total of 44 bacteria i.e., 6 Staphylococcus spp., 3 Enterococcus spp., 6 Bacillus spp., 4 Streptococcus spp., 6 Salmonella spp., and one from each genus including Escherichia, Acinetobacter, Pseudomonas, Proteus, Clostridioides, Candida, Brucella, Burkholderia, Francisella, Yersinia, Moraxella, Vibrio, Shigella, Serratia, Citrobacter, and Haemophilus (spp.) were discussed in the review for their identification using the above-mentioned techniques. Among all the identified microorganisms, 21% of studies have been conducted for the identification of E. coli, 14% for S. aureus followed by 37% for other microorganisms.