一类随机利率下特殊年金的计算

研究在随机利率相互独立条件下年金初值的计算问题,主要是研究各类年金初值的期望和方差的计算公式.文章给出了随机利率相互独立条件下期末付平顶虹式年金,期末付虹式年金,期末付倒平顶虹式年金和期末付倒虹式年金的初值公式及其简化关系,推导出了这类年金初值的各阶矩的简化公式,进而获得了这类年金初值的期望计算公式和方差计算公式.     

随机利息力下的一类年金的时间价值

对于年金的时间价值的研究,往往假定利率在整个期间内是固定不变的,但事实上,由于受到多种因素的影响,利率通常具有不确定性.因此,本文采用可逆MA(1)模型对随机利息力进行建模,在此基础上,研究了期末付虹式年金和期末付平顶虹式年金的时间价值问题,给出了上述两种形式年金现值的期望和方差的递推公式.通过数值仿真分析了相关参数对...     

随机利息力下的期末付倒平顶虹式年金

对于年金的定价问题的研究,传统精算理论假定利率是恒定不变的．但事实上,由于受到多种因素的影响,利率往往具有不确定性．因此,本文采用可逆MA（1）模型来刻画利率期限机构,在此基础上,研究了期末付倒平顶虹式年金的各阶矩问题,推导出了其年金现值的期望和方差的简洁公式．通过数值模拟分析了此年金面临的利率风险,其结论对年金定价有一定的参考价值．     

随机利率下的年金的计算

我们考虑随机利率下的一类延付年金在n年后的积累值的计算问题,目的在于研究积累值的期望和方差.本文给出两种方法计算在某些年内一类延付年金的积累值的期望和方差,获得了积累值的方差的递推关系,并且给出了计算公式.     

随机利率下年金的时间价值

本文首先在常数利率下讨论了递增年金、递减年金和固定增长年金的终值.进而在随机利率条件下研究了递增年金、递减年金和固定增长年金,得到了递增年金、递减年金和固定增长年金终值的期望与方差,推广了Zaks(2001)的结果.     

一类随机利率下的确定年金

我们考虑在一定的约束条件下利率是随机变量的某些确定年金的现值的计算问题,目的在于研究给付现值的期望和方差.本文给出两种方法计算在某些年内一类延付年金的现值之和的期望和方差,获得了给付现值的方差的递推关系,并且解决了这些关系,这在计算简单方面明显地更好.     

模糊随机环境下的连续型变额生命年金

采用模糊随机理论,构建连续支付型变额生命年金模型.假定利率为三角模糊数,死亡率为随机变量.结合精算理论,给出了连续支付型变额生命年金精算现值的期望、方差以及分布函数和分位数的模糊表达式.最后,通过实证分析计算出一个在养老保险中常见的生命年金的相关值,验证模型的可行性.     

一类随机利率模型下的年金精算现值

年金在日常生活中被广泛应用,但已往大多研究的是固定年金以及随机利率下的确定年金.本文在前人研究成果的基础上考虑了利率随机波动对生命年金的影响,运用随机利率模型,得出年金精算现值较为简单的递推关系式,并举例说明利率的随机波动对年金精算现值的影响程度,结果表明利率的波动对年金的定价影响非常大,绝对不容忽视.     

随机利率下的增额寿险模型研究

在实际的保险精算中,保单保险金现值函数的期望就是该种保单的纯保费,而方差常用来度量该种保单的风险.对随机利率采用W iener过程建模,得到了增额寿险保险金现值函数的期望和方差.     

农产品价格的随机模型及风险度量

在连续时间模型的假设条件下 ,研究了农产品价格服从伊藤随机过程的数学期望及方差问题 .首先利用 Fok ker-Planck方程及偏微分方程 ,经过变形对由该扩散随机过程所描述的价格均值及风险进行了估计 ;然后给出了假设 Ito随机过程为稳态条件下的转移概率密度 ps的表达式 ,利用 ps求出相应的价格与风险值 .该模型也可用于风险投资等领域的研究 .     

A moment-based analytic approximation of the risk-neutral density of American options

The price of a European option can be computed as the expected value of the payoff function under the risk-neutral measure. For American options and path-dependent options in general, this principle cannot be applied. In this paper, we derive a model-free analytical formula for the implied risk-neutral density based on the implied moments of the implicit European contract under which the expected value will be the price of the equivalent payoff with the American exercise condition. The risk-neutral density is semi-parametric as it is the result of applying the multivariate generalized Edgeworth expansion, where the moments of the American density are obtained by a reverse engineering application of the least-squares method. The theory of multivariate truncated moments is employed for approximating the option price, with important consequences for the hedging of variance, skewness and kurtosis swaps.     

模糊反向物流网络设计模型的一种改进遗传算法

反向物流是物流研究中的一个重要分支,其相关问题是目前研究的热点问题。该研究在模糊环境中根据不同的决策标准,建立了关于反向物流问题中的回收问题的三种不同类型的模型:期望值模型,机会约束模型和相关机会模型,并设计了一个模糊模拟和遗传算法相结合的混合智能算法来解决提出的模型,最后给出了一个数值例子,结果证明了将此混合智能算法用于求解模糊反向物流网络设计模型问题的有效性。     

Some modifications of improved estimators of a normal variance

Consider the problem of estimating a normal variance based on a random sample when the mean is unknown. Scale equivariant estimators which improve upon the best scale and translation equivariant one have been proposed by several authors for various loss functions including quadratic loss. However, at least for quadratic loss function, improvement is not much. Herein, some methods are proposed to construct improving estimators which are not scale equivariant and are expected to be considerably better when the true variance value is close to the specified one. The idea behind the methods is to modify improving equivariant shrinkage estimators, so that the resulting ones shrink little when the usual estimate is less than the specified value and shrink much more otherwise. Sufficient conditions are given for the estimators to dominate the best scale and translation equivariant rule under the quadratic loss and the entropy loss. Further, some results of a Monte Carlo experiment are reported which show the significant improvements by the proposed estimators.     

Mean and variance optimization of non–linear systems and worst–case analysis

In this paper, we consider expected value, variance and worst–case optimization of nonlinear models. We present algorithms for computing optimal expected value, and variance policies, based on iterative Taylor expansions. We establish convergence and consider the relative merits of policies based on expected value optimization and worst–case robustness. The latter is a minimax strategy and ensures optimal cover in view of the worst–case scenario(s) while the former is optimal expected performance in a stochastic setting. Both approaches are used with a small macroeconomic model to illustrate relative performance, robustness and trade-offs between the alternative policies.     

Further Results for Closed Cyclic Queues with Balanced Exponential Servers

This note presents some new results for closed cyclic queues with balanced exponential servers. The probability density function, expected value, variance and coefficient of variation of conditional idle time, residual idle time, time in a stage, cycle time and waiting time are presented. Conditional waiting time, residual waiting time and interdeparture time results are obtained from the dual.     

Generalizing variance to allow the inclusion of decision attitude in decision making under uncertainty

The problem of decision making under uncertainty is considered. It is noted that an alternative is described in terms of an uncertainty profile. We observe that a major difficulty in the decision process is the comparison of these uncertainty profiles. We discuss the need for introducing some features of an uncertainty profile to help simplify this comparison. We note that the quantification of these simplifying features involves some subjective considerations about the decision makers preferences. We introduce the idea of the decision maker’s attitudinal character to help in the formulation of these considerations. We then investigate two important features associated with an uncertainty profile. The first, the representative value, is a generalization of expected value commonly used under probabilistic uncertainty. The second, called the measure of deviation, provides a generalization of the concept of variance. We show how these new measures allows us to consider uncertainty profiles other then just the probabilistic one. They also allow us introduce other decision maker attitudes then the one implicitly assumed with the expected value and variance.     

Error control process in function interpolation using statistical spline model

In this paper, we propose an algebraic method based on solving some inequalities of polynomial type to control the error value of interpolation formulas whose residue depends on a monic polynomial. This method then leads to construct some piecewise approximations (splines) of statistical type, which are based on a specific partition of the main interval. In other words, in this model of spline, approximate criteria are considered fixed and sub-intervals corresponding to criteria are derived as accurately as possible. In this sense, some statistical concepts such as expected value, variance measure, skewness and kurtosis coefficients are also inserted into the definition of statistical splines. Finally, a numerical results section is separately given to confirm all results in the paper.