广西经济增长、金融发展与城乡收入差距的实证研究

探讨了经济增长及金融发展与城乡收入差距之间互动影响,刻画了三者间的逻辑关系,并基于广西1990-2017年的统计数据,运用状态空间模型及卡尔曼滤波算法对三者间动态关系进行了实证分析.结果显示:经济增长对城乡收入差距呈现倒U型曲线形态,而金融发展则显示出具有不断缩小城乡收入差距的趋势.     

基于贝叶斯网络的船舶港口国监督检查滞留风险研究

针对港口国监督(Port State Control, PSC)检查的复杂性和不确定性, 基于贝叶斯网络理论构建船舶PSC检查滞留风险分析模型. 以东京备忘录(Tokyo MOU)中2014~2017年船舶PSC检查样本数据为基础, 运用R语言bnlearn包进行贝叶斯网络的结构及参数学习. 同时分别执行贝叶斯网络的正向、逆向推理, 定量表示各风险因素与滞留结果之间的相互作用关系, 找出导致船舶滞留的高风险因素, 实现不确定环境下船舶PSC检查滞留风险的全面动态分析. 实证表明, 模型具有较高的精确度, 可为检查人员的滞留决策及航运公司的安全风险管理提供有效依据.     

Information Network Modeling for U.S. Banking Systemic Risk

In this work we investigate whether information theory measures like mutual information and transfer entropy, extracted from a bank network, Granger cause financial stress indexes like LIBOR-OIS (London Interbank Offered Rate-Overnight Index Swap) spread, STLFSI (St. Louis Fed Financial Stress Index) and USD/CHF (USA Dollar/Swiss Franc) exchange rate. The information theory measures are extracted from a Gaussian Graphical Model constructed from daily stock time series of the top 74 listed US banks. The graphical model is calculated with a recently developed algorithm (LoGo) which provides very fast inference model that allows us to update the graphical model each market day. We therefore can generate daily time series of mutual information and transfer entropy for each bank of the network. The Granger causality between the bank related measures and the financial stress indexes is investigated with both standard Granger-causality and Partial Granger-causality conditioned on control measures representative of the general economy conditions.     

Determination,residue and risk assessment of trifloxystrobin,trifloxystrobin acid and tebuconazole in Chinese rice consumption

A simple and rapid analytical method for the detection of trifloxystrobin, trifloxystrobin acid and tebuconazole in soil, brown rice, paddy plants and rice hulls was established and validated by liquid chromatography with tandem mass spectrometry. Acceptable linearity (R² > 0.99), accuracy (average recoveries of 74.3–108.5%) and precision (intra- and inter-day relative standard deviations of 0.9–8.8%) were obtained using the developed determination approach. In the field trial, the half-lives of trifloxystrobin and tebuconazole in paddy plants were 5.7–8.3 days in three locations throughout China, and the terminal residue concentrations of trifloxystrobin and tebuconazole were <100 and 500 μg/kg (maximum residue limits set by China), respectively, at harvest, which indicated that, based on the recommended application procedure, trifloxystrobin and tebuconazole are safe for use on rice. The risk assessment results demonstrated that, owing to risk quotient values of both fungicides being <100%, the potential risk of trifloxystrobin and tebuconazole on rice was acceptable for Chinese consumers. These data could provide supporting information for the proper use and safety evaluation of trifloxystrobin and tebuconazole in rice.     

Residues,dissipation and risk evaluation of spiroxamine in open-field-grown strawberries using liquid chromatography tandem mass spectrometry

The dissipation dynamic and residues of spiroxamine in open-field-grown strawberries were determined using liquid chromatography tandem mass spectrometry (LC–MS/MS). Spiroxamine application was performed according to Egyptian good agricultural practices recommendation. A QuEChERS-based extraction method along with direct analysis with an LC–MS/MS analytical method were optimized and validated, and the specificity of the techniques used was considered satisfactory. Good linearity (R² > 0.999) was obtained for spiroxamine within the range of 0.001–0.1 μg/ml. The mean recoveries varied between 97.1 and 108.2%, with inter- and intra-day precision (RSD) <4.9%. The limit of quantitation for spiroxamine was 0.001 mg/kg. The results indicated that spiroxamine degradation in strawberry followed first–order kinetics (R² > 0.9929) with an estimated half-life value of 4.71 days. Considering the Australian maximum residue limit (0.05 mg/kg) in strawberry and based on the results from residue trials with a preharvest interval of 14 days for strawberry, compliance can be expected. The present results could provide guidance to fully evaluate the risks of spiroxamine residues, preventing any potential health risk to consumers.     

Collective risk models with dependence

In actuarial science, collective risk models, in which the aggregate claim amount of a portfolio is defined in terms of random sums, play a crucial role. In these models, it is common to assume that the number of claims and their amounts are independent, even if this might not always be the case. We consider collective risk models with different dependence structures. Due to the importance of such risk models in an actuarial setting, we first investigate a collective risk model with dependence involving the family of multivariate mixed Erlang distributions. Other models based on mixtures involving bivariate and multivariate copulas in a more general setting are then presented. These different structures allow to link the number of claims to each claim amount, and to quantify the aggregate claim loss. Then, we use Archimedean and hierarchical Archimedean copulas in collective risk models, to model the dependence between the claim number random variable and the claim amount random variables involved in the random sum. Such dependence structures allow us to derive a computational methodology for the assessment of the aggregate claim amount. While being very flexible, this methodology is easy to implement, and can easily fit more complicated hierarchical structures.     

Bayesian Estimation and Statistical Analysis of Risk Measurements

The Bayesian model are established for the VaR and related risk measurements. The relationship between VaR and other risk measurements including expect shortfall, tail condition expectation and conditional value at risk are discussed. Furthermore, the Bayesian estimates and Bayesian predictors of these risk measurement are derived. Thirdly, the consistency and asymptotic normality in the exponential risk model are proved. Finally, the numerical simulation method is used to verify the convergence rate under different sample sizes.