基于不确定控制理论的最优策略研究

本文在不确定理论的框架下,研究一类带背景状态变量的最优控制模型.在乐观值准则下,利用不确定动态规划的方法,证明了不确定最优性原则,得到最优性方程.作为应用,求解一个固定缴费(DC)型养老金的最优投资策略问题,在乐观值准则下,以工资变量为背景状态变量,建立养老金模型.通过求解不确定最优性方程得到最优投资策略和最优支付率.     

ON THE EXPECTED DISCOUNTED PENALTY FUNCTION IN A MARKOV-DEPENDENT RISK MODEL WITH CONSTANT DIVIDEND BARRIER

This article considers a Markov-dependent risk model with a constant dividend barrier. A system of integro-differential equations with boundary conditions satisfied by the expected discounted penalty function, with given initial environment state, is derived and solved. Explicit formulas for the discounted penalty function are obtained when the initial surplus is zero or when all the claim amount distributions are from rational family. In two state model, numerical illustrations with exponential claim amounts are given.     

带干扰的Erlang（2）风险模型破产概率的分解

本文研究了带干扰的Erlang(2)风险模型的破产概率.利用延迟更新方法以及全概率公式,获得了积分表达式、二次连续可微性以及微分方程,并且讨论了索赔额分布为指数分布时的情形.     

DURATION OF NEGATIVE SURPLUS FOR A TWO STATE MARKOV-MODULATED RISK MODEL

We consider a continuous time risk model based on a two state Markov process, in which after an exponentially distributed time, the claim frequency changes to a different level and can change back again in the same way. We derive the Laplace transform for the first passage time to surplus zero from a given negative surplus and for the duration of negative surplus. Closed-form expressions are given in the case of exponential individual claim. Finally, numerical results are provided to show how to estimate the moments of duration of negative surplus.     

重尾β混合随机变量序列的大偏差

设{X_n; n≥1}是重尾平稳非负随机变量序列, 研究其部分和 S_n=X₁+X₂+…+X_n的对数渐近性质. 对于适当的x, 在混合条件下, 给出了估计P(Sn>n^x)≈n^−αx+1, 其中α是特定的参数. 验证了Gantert提出的相关的猜想, 并且证明了所谓的上确界大偏差原理.     

经典风险模型中破产概率的一个渐近式

本文研究经典风险模型中破产概率的渐近行为．利用几何和的方法，获得了索赔额的分布属于S（γ）．γ〉0。时破产概率的一个局部渐近式．同时．给出了一个具体的数值的例子．     

独立随机变量部分和的大偏差概率的估计

设｛Ｘｎ｝ｎ≥１是一列相互独立且具有相同分布、非负非退化的随机变量序列．Ｓ＝Ｘ１＋…＋Ｘｎ，μＥＸ１，ａ是Ｘ１的分布支撑的上确界．假设ＥｅｕＸ１＜∞，ｕ＞０．对μ＜Ｘｎ＜ａ，本文分别讨论了１ｏｇＰ｛Ｓｎ≥ｎｘｎ｝及Ｐ｛Ｓｎ≥ｎｘｎ｝Ｊ当ｎ→∞时的渐近性质。     

随机发展方程小扰动大偏差原理的统一方法

设X^ε=|X^ε(t);0≤t≤1|(ε>0)是由随机发展方程 dX^ε(t)=^ε(1/2)σ(X^ε(t))dB(t)+b(X^ε(t),ν(t))dt控制的随机过程,其中ν(t)是与Brown运动B(·)独立的随机过程。讨论了|(X^ε,ν(·));ε>0|的大偏差性质;在特殊情形下,给出了精确的速率函数,解决了Eizenberg和Freidlin所提的一个问题。此外,还得到一个一般性大偏差定理。     

Large deviations for heavy-tailed random sums of independent random variables with dominatedly varying tails

We prove large deviation results on the partial and random sums Sn = ∑i=1n Xi,n≥1; S(t) = ∑i=1N(t) Xi, t≥0, where {N(t);t≥0} are non-negative integer-valued random variables and {Xn;n≥1} are independent non-negative random variables with distribution, Fn, of Xn, independent of {N(t); t≥0}. Special attention is paid to the distribution of dominated variation.     

下模(上模)不可加测度的条件期望(英文)

本文研究了下模(上模)不可加测度的条件期望.利用下模不可加测度μ的Choquet积分的最大可加表示定理定义了下模(上模)不可加测度的条件期望, 并且证明了这种条件期望的相关性质.