跳扩散盈余过程的最优投资和最优再保险

站在保险人的立场上,研究了跳扩散盈余过程的最优投资和最优再保险问题.在方差保费原理下,以盈余终值的期望指数效用达到最大作为最优准则,给出了最优策略和值函数的近似表达式.同时也证明了投资总比不投资好的结论.最后,通过一些数例和图表来进一步说明所获得的结论.     

马尔柯夫决策规划的强最优准则

本文研究离散参量马尔柯夫决策规划问题.文中把通常按数学期望下的平均总报酬的平均目标最优准则,称为“弱最优”的.同时提出了按样本过程(或实现)的实际平均总报酬的“准强最优”与“强最优”准则.讨论了它们之间的关系及在什么条件下弱最优策略,也是准强最优、强最优的.证明了目前常用的两个弱最优策略存在的充分条件,也是在上强最优策略存在的充分条件,等等.     

离散时间马氏决策过程的首达目标准则

本文考虑可数状态离散时间马氏决策过程的首达目标模型的风险概率准则.优化的准则是最小化系统首次到达目标状态集的时间不超过某阈值的风险概率.首先建立最优方程并且证明最优值函数和最优方程的解对应,然后讨论了最优策略的一些性质,并进一步给出了最优平稳策略存在的条件,最后用一个例子说明我们的结果.     

具有随机投资收益的离散风险模型的最优红利分配

本文讨论的是离散模型下以期望累计红利最大化为目标的最优红利分配政策,通过Bellman最优性准则,我们得到了最优值函数满足的动态规划方程并结合实例给出了求解这些方程的算法.     

基于索赔相依的时滞均衡投资与再保险策略

本文研究保险公司的最优投资与再保险问题.假设再保险种类是比例再保险,未来索赔与历史索赔是相关的.此外,风险资产的价格过程由常方差弹性模型来描述,并且在财富过程中考虑了财富的时滞效应.在均值-方差优化准则下,本文给出了最优均衡投资和比例再保险策略及值函数的显式解.最后,通过数值分析,讨论了模型主要参数对最优策略的影响.本文所提模型及所获结果是对文献中已有研究成果的推广.     

风险相依下再保险双方的联合最优再保险问题

结合保险人和再保险人的共同利益,研究了具有两类相依险种风险模型下的最优再保险问题.假定再保险公司采用方差保费原理收取保费,利用复合Poisson模型和扩散逼近模型两种方式去刻画保险公司和再保险公司的资本盈余过程,在期望效用最大准则下,证明了最优再保险策略的存在性和唯一性,通过求解Hamilton-Jacobi-Bellman（HJB）方程,得到了两种模型下相应的最优再保险策略及值函数的明晰解答,并给出了数值算例及分析.     

部分因析裂区设计最优分区组的理论

在最小低阶混杂和最大估计能力这两个准则下,研究了部分因析裂区(FFSP)设计的最优分区组的问题. 为了区分非同构的分区组FFSP设计发展了最小附加混杂(MSA)和最大附加估计能力(MSEC)准则, 并建立了通过分区组的参照设计来识别MSA或MSEC分区组FFSP设计的一般规则.     

风险相依下再保险双方的联合最优再保险问题

结合保险人和再保险人的共同利益,研究了具有两类相依险种风险模型下的最优再保险问题.假定再保险公司采用方差保费原理收取保费,利用复合Poisson模型和扩散逼近模型两种方式去刻画保险公司和再保险公司的资本盈余过程,在期望效用最大准则下,证明了最优再保险策略的存在性和唯一性,通过求解Hamilton-Jacobi-Bellman(HJB)方程,得到了两种模型下相应的最优再保险策略及值函数的明晰解答,并给出了数值算例及分析.     

基于新巴塞尔协议监管下保险人的均值-方差最优投资-再保险问题

本文研究了均值-方差优化准则下,保险人的最优投资和最优再保险问题.我们用一个复合泊松过程模型来拟合保险人的风险过程,保险人可以投资无风险资产和价格服从跳跃-扩散过程的风险资产.此外保险人还可以购买新的业务(如再保险).本文的限制条件为投资和再保险策略均非负,即不允许卖空风险资产,且再保险的比例系数非负.除此之外,本文还引入了新巴塞尔协议对风险资产进行监管,使用随机二次线性(linear-quadratic,LQ)控制理论推导出最优值和最优策略.对应的哈密顿-雅克比-贝尔曼(Hamilton-Jacobi-Bellman,HJB)方程不再有古典解.在粘性解的框架下,我们给出了新的验证定理,并得到有效策略(最优投资策略和最优再保险策略)的显式解和有效前沿.     

广义部分线性单指标模型的最优模型平均方法

本文研究广义部分线性单指标模型(generalized partially linear single-index models, GPLSIMs)的模型平均问题.在实际应用中, GPLSIMs由于其灵活性和易解释性受到广泛关注.然而, GPLSIMs在应用中存在两类不确定性:变量的不确定性和单指标连接函数光滑度的不确定性.为了解决该不确定性问题,本文提出一种GPLSIMs的最优模型平均方法,该方法通过最大交叉验证准则得到数据驱动的权重.在模型误设定假设和发散模型空间的框架下,本文证明在最小化Kullback-Leibler (KL)损失准则下,所提出的模型平均估计渐近最优.同时,当候选模型集中存在伪真模型时,本文证明基于交叉验证准则得到的权重渐近地集中在伪真模型上.此外,基于提出的模型平均方法,本文为GPLSIMs构建了一种变量重要性度量,并证明该度量可以渐近识别所有真实模型中的变量.模拟研究和两个实际数据分析均展示了本文提出的方法相对于几种现有方法的优势.     

基于鲁棒均值-下半偏差模型的供电公司购电组合策略

电力市场中,日前市场购电电价的随机波动,给供电公司的投资带来了一定的收益风险,因而供电公司需要在不同的市场中合理分配购电电量分散投资,以实现自身收益率尽可能大的同时承受的风险最小.供电公司在多市场中购电电价呈随机波动的特性,本文用均值-下半偏差作为购电风险测度,并用鲁棒优化处理电价的不确定性,建立了供电公司鲁棒均值-下半偏差(Robust Mean Semi-Deviation)购电策略优化模型.最后利用广西电网公司提供的数据进行实证分析,验证了模型的有效性和适用性,表明此模型对供电公司的投资组合决策具有一定的参考价值和指导意义.     

Determining the best strategy for changing the configuration of a football team

This paper proposes a dynamic programming (DP) approach to find the optimal substitution strategy for a football match, which maximises the probability of winning or the expected number of league points, supported by real data of the English Premier League. We use a Markov process model to evaluate the offensive and defensive strengths of teams by means of maximum likelihood estimators. We develop a DP formulation to derive quantitatively the optimal substitution strategy of a team, in relation to the number required of each type of outfield player. We demonstrate how this approach may help to determine how many of each type of player should start a match and be substituted during a match. We also show how the expected league points would increase if the optimal strategy were followed.     

多约束下的串、并联混合系统可靠度与冗余度的优化判定模型及算法

本文给出了单目标多约束下串、并联混合系统中 ,由选取重要单元 (重要度最大的单元 )的方法 ,来提高系统可靠度的有效优化判定模型及算法 ,用同样思想给出了串、并联系统中冗余度的优化判定模型及算法     

Economic manufacturing quantity,optimum process mean,and economic specification limits setting under the rectifying inspection plan

Economic manufacturing quantity, process mean, and specification limits setting are three important methods for the inventory and quality control problems. In the imperfect production system, we usually consider the manufacturing quantity for reducing the inventory cost, determine the process level for reducing the production cost, and select the specification limits for screening the products. In this paper, we propose the above integrated model based on the application of rectifying inspection plan for obtaining maximum expected total profit of product. The asymmetric quadratic quality loss function is adopted for measuring the product quality. The sensitivity analyses of parameters are provided for illustration.     

On the geometry of linear Weingarten hypersurfaces in the hyperbolic space

In this paper, we apply some forms of generalized maximum principles in order to study the geometry of complete linear Weingarten hypersurfaces with nonnegative sectional curvature immersed in the hyperbolic space. In this setting, under the assumption that the mean curvature attains its maximum, we prove that such a hypersurface must be either totally umbilical or isometric to a hyperbolic cylinder.     

Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models

A computationally simple approach to inference in state space models is proposed, using approximate Bayesian computation (ABC). ABC avoids evaluation of an intractable likelihood by matching summary statistics for the observed data with statistics computed from data simulated from the true process, based on parameter draws from the prior. Draws that produce a “match” between observed and simulated summaries are retained, and used to estimate the inaccessible posterior. With no reduction to a low-dimensional set ofsufficient statistics being possible in the state space setting, we define the summaries as the maximum of an auxiliary likelihood function, and thereby exploit the asymptotic sufficiency of this estimator for the auxiliary parameter vector. We derive conditions under which this approach—including a computationally efficient version based on the auxiliary score—achieves Bayesian consistency. To reduce the well-documented inaccuracy of ABC in multiparameter settings, we propose the separate treatment of each parameter dimension using an integrated likelihood technique. Three stochastic volatility models for which exact Bayesian inference is either computationally challenging, or infeasible, are used for illustration. We demonstrate that our approach compares favorably against an extensive set of approximate and exact comparators. An empirical illustration completes the article. Supplementary materials for this article are available online.     

Revenue-maximizing Dutch auctions with discrete bid levels

This paper is concerned with setting a predetermined number of bid levels in a Dutch auction to maximize the auctioneer’s expected revenue. As a departure from the traditional methods used by applied economists and game-theorists, a novel approach is taken in this study to tackle the problem by formulating the auctioning process as a constrained nonlinear program and applying standard optimization techniques to solve it. Aside from proposing respective closed-form formulae for computing the optimal bid levels and the auctioneer’s maximum expected revenue, we also show that the bid decrements should be increasing if there are two or more bidders in the Dutch auction. Additionally, the auctioneer’s maximum expected revenue increases with the number of bidders as well as the number of bid levels. Finally, managerial implications of the key findings as well as limitations of this research work are discussed.     

Using a Markov process model of an association football match to determine the optimal timing of substitution and tactical decisions

A football match is modelled as a four-state Markov process. A log-linear model, fed by real data, is used to estimate transition probabilities by means of the maximum likelihood method. This makes it possible to estimate the probability distributions of goals scored and the expected number of league points gained, from any position in a match, for any given set of transition probabilities and hence in principle for any match. This approach is developed in order to estimate the optimal time to change tactics using dynamic programming, either by making a substitution or by some other conscious change of plan. A simple example of this approach is included as an illustration.     

非扩张映象有限族的公共不动点的隐式迭代方法

本文在实一致凸和q一致光滑Banach空间中研究了一类新的有限族非扩张映象的公共不动点的具误差和具扰动映射的隐式迭代程序并且得到了一些收敛性定理.特别地,获得了该隐式迭代程序强收敛性的充要条件.本文所得结论推广了文[1,2]中的相应结果.     

Fixed point results for generalized quasicontraction mappings in abstract metric spaces

In this paper, we introduce the concept of generalized quasicontraction mappings in an abstract metric space. By using this concept, we construct an iterative process which converges to a unique fixed point of these mappings. The result presented in this paper generalizes the Banach contraction principle in the setting of metric space and a recent result of Huang-Zhang for contractions. We also validate our main result by an example.