农产品中6种有机溶剂残留的气相色谱-质谱检测方法

建立了蔬菜、粮食等农产品中6种有机溶剂残留(甲苯、邻二甲苯、间二甲苯、对二甲苯、N,N-二甲基甲酰胺(DMF)和二甲基亚砜(DMSO)的液液萃取/气相色谱-质谱分析方法。不同类型的样品经乙腈-水溶液或乙腈溶剂提取后,用Agilent DB-624(30.0 m×250μm×1.4μm)毛细管色谱柱分离,在GC-MS选择离子监测(SIM)模式下检测,以保留时间和特征离子丰度比定性,外标法定量。结果表明,该方法对不同样品中4种苯系物在0.005~0.500 mg/L,DMF在0.025~0.125 mg/L,DMSO在0.050~0.500 mg/L浓度范围内线性关系良好,相关系数(r)为0.992 0~0.997 1。6种有机溶剂的平均加标回收率为60.1%~115.2%,相对标准偏差不大于11.0%。苯系物、DMF和DMSO的方法检出限(S/N=3)分别为0.002~0.050,0.010~0.025,0.060~0.150 mg/kg。该方法准确、快速、灵敏,可用于各种农产品中有机溶剂残留的监控。     

城镇职工养老保险随机模型研究

构建了包含个人、企业、政府等市场参与者相互制衡的城镇职工养老保险随机模型,该模型涉及了储蓄、工作期消费、个人养老金账户、工资、退休后消费共5个随机变量;利用ITo引理证明了随机微分方程解的存在性,唯一性,利用2010-2014年中国有关宏观数据,对5个变量进行了动态模拟,并对部分参数变动对模型的影响进行分析,得出了储蓄替代率和人口出生率与两期消费正相关,两者的小范围变动不会影响两期消费的趋势等结论.     

基于向后逐步回归模型的我国农机需求特征及影响因素研究

以2004-2014年数据为样本,以农机总动力为因变量,以农机购置补贴、农机价格、农机作业服务价格、农户人均纯收入、农产品价格、农业劳动力数量和农作物播种总面积为自变量构建了我国农机需求影响因素的回归方程,向后逐步回归结果表明:(1)除农作物播种总面积、农机作业服务价格、农产品价格之外,其余变量对农机总动力的影响均统计上显著;(2)农机购置补贴、农机价格指数、农户人均纯收入及农业劳动力四个变量对农机需求的弹性系数分别为0.027、-0.004、0.457、0.474。最后根据研究结果提出加大与落实农机购置补贴、规范农机价格、培育新型经营主体、加速土地规范流转等政策建议。     

车险费率厘定精算技术的研究与应用评述

精算技术为中国车险市场费率改革提供必要支持,可以确保费率厘定的科学性与合理性。首先,本文系统梳理了车险分类风险费率厘定精算统计模型的发展历程,并回顾参数估计方法。其次,论述了车险个体风险费率厘定的精算模型与方法,并重点评述了信度理论与奖惩系统的研究。进而,归纳出车险费率厘定精算统计模型的研究热点与发展方向。最后,指明现有研究对中国车险费率厘定精算方法的启示,并提出相关建议。     

Analysis of survivorship life insurance portfolios with stochastic rates of return

A general portfolio of survivorship life insurance contracts is studied in a stochastic rate of return environment with a dependent mortality model. Two methods are used to derive the first two moments of the prospective loss random variable. The first one is based on the individual loss random variables while the second one studies annual stochastic cash flows. The distribution function of the present value of future losses at a given valuation time is derived. For illustrative purposes, an AR(1) process is used to model the stochastic rates of return, and the future lifetimes of a couple are assumed to follow a copula model. The effects of the mortality dependence, the portfolio size and the policy type, as well as the impact of investment strategies on the riskiness of portfolios of survivorship life insurance policies are analyzed by means of moments and probability distributions.     

Unit-linked life insurance policies: Optimal hedging in partially observable market models

In this paper we investigate the hedging problem of a unit-linked life insurance contract via the local risk-minimization approach, when the insurer has a restricted information on the market. In particular, we consider an endowment insurance contract, that is a combination of a term insurance policy and a pure endowment, whose final value depends on the trend of a stock market where the premia the policyholder pays are invested. To allow for mutual dependence between the financial and the insurance markets, we use the progressive enlargement of filtration approach. We assume that the stock price process dynamics depends on an exogenous unobservable stochastic factor that also influences the mortality rate of the policyholder. We characterize the optimal hedging strategy in terms of the integrand in the Galtchouk–Kunita–Watanabe decomposition of the insurance claim with respect to the minimal martingale measure and the available information flow. We provide an explicit formula by means of predictable projection of the corresponding hedging strategy under full information with respect to the natural filtration of the risky asset price and the minimal martingale measure. Finally, we discuss applications in a Markovian setting via filtering.     

科技保险中项目投资损失保险投保比例优化决策

针对我国科技保险第二批推行险种--项目投资损失保险,以科技企业为研究主体,综合考虑其期望利润和科技风险(方差),构建了投保比例模型.在对武汉市迪源光电科技有限公司投保科技保险的具体案例中,运用线性不等式组的旋转算法进行求解,计算出企业在项目组合投资中如何优化各项投保比例,使其以最小的风险承担得到最大的期望利润.     

Subgroup analysis of zero-inflated Poisson regression model with applications to insurance data

Customized personal rate offering is of growing importance in the insurance industry. To achieve this, an important step is to identify subgroups of insureds from the corresponding heterogeneous claim frequency data. In this paper, a penalized Poisson regression approach for subgroup analysis in claim frequency data is proposed. Subjects are assumed to follow a zero-inflated Poisson regression model with group-specific intercepts, which capture group characteristics of claim frequency. A penalized likelihood function is derived and optimized to identify the group-specific intercepts and effects of individual covariates. To handle the challenges arising from the optimization of the penalized likelihood function, an alternating direction method of multipliers algorithm is developed and its convergence is established. Simulation studies and real applications are provided for illustrations.     

Optimal investment of DC pension plan under short-selling constraints and portfolio insurance

In this paper we investigate an optimal investment problem under short-selling and portfolio insurance constraints faced by a defined contribution pension fund manager who is loss averse. The financial market consists of a cash bond, an indexed bond and a stock. The manager aims to maximize the expected S-shaped utility of the terminal wealth exceeding a minimum guarantee. We apply the dual control method to solve the problem and derive the representations of the optimal wealth process and trading strategies in terms of the dual controlled process and the dual value function. We also perform some numerical tests and show how the S-shaped utility, the short-selling constraints and the portfolio insurance impact the optimal terminal wealth.     

Budget-constrained optimal insurance with belief heterogeneity

We re-examine the problem of budget-constrained demand for insurance indemnification when the insured and the insurer disagree about the likelihoods associated with the realizations of the insurable loss. For ease of comparison with the classical literature, we adopt the original setting of Arrow (1971), but allow for divergence in beliefs between the insurer and the insured; and in particular for singularity between these beliefs, that is, disagreement about zero-probability events. We do not impose the no sabotage condition on admissible indemnities. Instead, we impose a state-verification cost that the insurer can incur in order to verify the loss severity, which rules out ex post moral hazard issues that could otherwise arise from possible misreporting of the loss by the insured. Under a mild consistency requirement between these beliefs that is weaker than the Monotone Likelihood Ratio (MLR) condition, we characterize the optimal indemnity and show that it has a simple two-part structure: full insurance on an event to which the insurer assigns zero probability, and a variable deductible on the complement of this event, which depends on the state of the world through a likelihood ratio. The latter is obtained from a Lebesgue decomposition of the insured’s belief with respect to the insurer’s belief.