条件自回归利率下缴费预定型企业年金保险的生存年金精算现值模型

本文利用时间序列理论将投资利率为条件AR(1)模型推广为条件AR(p)模型,并利用生存年金理论得到缴费预定型企业年金保险中相应利率下的生存年金精算现值模型,这对解决企业合理发放养老金,避免企业养老基金出现赤字等问题具有重要理论指导意义和实际应用价值.     

ARMA，(1，1)利息力下缴费确定型企业生存年金的精算现值模型

本文是在AR(1)、MA(1)的基础上对条件自回归移动平均模型ARMA(1,1)利息力下缴费确定性生存年金精算现值模型的研究,综合了AR(1)和MA(1)两个模型的优点。这对我国处于初步阶段的企业年金的发展具有理论指导和实际应用价值。     

Erlang风险模型有限时间的破产概率

Erlang风险模型广泛应用于排队论、控制论以及金融风险过程.本文在索赔来到(claim-arrival)为Erlang过程,索赔额服从帕雷托分布以及具有常数利息力度的假设下,得到了有限时间内破产概率的渐近表达公式.该结果实质性地推广了Kluppelberg and Stadtmuller[1]和Tang[2]的结果:前者考虑了无穷时间的破产概率,而后者考虑的过程局限为泊松的.由破产模型与排队模型之间的联系可知,本文的结果在管理科学中有许多应用.     

随机利率下的寿险模型研究

建立了一个随机利率下的综合寿险模型,把几种保险产品统一在其中,模型包括延期支付的年金部分、终身寿险部分、还本部分;考虑利息力函数是一个随机过程;可以根据实际情况调整参数,通过不同参数的组合,获得不同的随机利率下的保险产品.     

随机利率下的终身寿险模型

在传统的精算模型中,常常假定利率固定不变,并基于此来进行产品的设计和准备金的提取。但现实中利率确实经常变动的,为了建立一个能够规避利率风险的模型,本文对利率的随机性采取反射布朗运动建模,在将其引入传统精算模型,得出了全连续式增额寿险模型纯保费和责任准备金的一般表达式。     

经济时间资产定价模型

在常规时间变换研究中所采用的从属概念是建立在独立条件上的,但是价格和成交量之间却是相关的.为了能够将成交量作为价格的随机时间,推广了从属概念,提出了相关从属的定义.相关从属扩大了时间变换研究的范围.继而讨论了相关从属下过程的扩散性质,研究了经济时间上的资产定价问题,结果类似于资本资产定价模型和套利定价模型.最后,利用零...     

基于小波变换的长记忆随机波动模型估计方法研究

根据ARFIMA过程的小波分析结果,将小波引入到长记忆随机波动(Long Memory Stochastic Volatility)LMSV模型的估计中,提出了基于小波变换的LMSV模型的参数估计和潜在波动过程的估计方法.用不同参数值和样本容量的数据进行了模拟实验,又用该方法对上海和深圳证券交易所综合指数的收益序列拟合了LMSV模型,结果表明该方法是有效且可行的.     

二元风险模型下的保险公司最优投资策略

本文考虑了二元风险模型下保险公司的投资问题.假设保险公司的两个子公司分别在风险市场上投资,且投资策略都属于常数族,利用鞅方法得到了破产概率的指数型上界,给控制保险公司的风险提供了可能.并且得到了最优的常数投资策略,该策略可以使破产概率的上界最小.最后给出了具体的算例阐述了本文的结果.     

随机旅行时间局内车辆路径问题的模型及其算法

人们在生活中会经常遇到随机旅行时间的局内车辆路径问题,如现实物流配送中的交通堵塞现象.文章在Laporte等的研究基础上,提出了一个考虑堵塞点动态产生、一个个遇到,堵塞时间为随机变量的模型,并构造了求解该模型的算法.     

浅析我国寿险公司企业年金的问题与对策

企业年金作为企业为员工提供的养老补充保险以及福利计划的一项重要内容,越来越为人们所关注。本文在分析影响寿险公司企业年金发展因素的基础上,提出了完善寿险公司企业年金发展的建议。     

Forecasting industrial production using structural time series models

Industrial production data series are volatile and often also cyclical. Hence, univariate time series models which allow for these features are expected to generate relatively accurate forecasts of industrial production. A particular class of unobservable components models — structural time series models — is used to generate forecasts of Austrian and German industrial production. A widely applied ARIMA model is used as a baseline for comparison. The empirical results show that the basic structural model generates more accurate forecasts than the ARIMA model when accuracy is measured in terms of size of error or directional change; and that the basic structural model forecasts better than the structural model with a cyclical component included on the basis of numerical measures, and tracking error for month-to-month changes.     

语言多属性决策的目标规划模型

研究了只有部分属性权重信息、属性值以语言变量或不确定语言变量形式给出且决策者对方案有偏好信息的语言多属性决策问题.给出了语言变量和不确定语言变量的运算法则,以及不确定语言变量之间比较的可能度公式,定义了语言变量的偏离度概念.在属性值以1)语言变量和2)不确定语言变量,这两种形式给出的情形下,分别建立了一个基于偏离度的目标规划模型,并通过求解这两种模型分别获得相应的属性权重.然后对于情形1),利用语言加权平均(LWA)算子,对语言决策信息进行加权集成,继而对方案进行排序和择优;对于情形2),利用不确定语言加权平均(ULWA)算子,对不确定语言决策信息进行加权集成,并利用可能度公式构造可能度矩阵(互补判断矩阵),继而利用互补判断矩阵排序公式对决策方案进行排序和择优.最后进行了实例分析.     

Multi-depot vehicle routing problem with time windows under shared depot resources

A new variant of multi-depot vehicle routing problem with time windows is studied. In the new variant, the depot where the vehicle ends is flexible, namely, it is not entirely the same as the depot that it starts from. An integer programming model is formulated with the minimum total traveling cost under the constrains of time window, capacity and route duration of the vehicle, the fleet size and the number of parking spaces of each depot. As the problem is an NP-Hard problem, a hybrid genetic algorithm with adaptive local search is proposed to solve it. Finally, the computational results show that the proposed method is competitive in terms of solution quality. Compared with the classic MDVRPTW, allowing flexible choice of the stop depot can further reduce total traveling cost.     

Optimal payment time under permissible delay in payment for products with deterioration

A permissible credit period is usually allowed to a retailer to pay back the dues without paying any interest to the supplier. The retailer can pay the supplier either at the end of the credit period or later incurring interest charges on the unpaid balance for the overdue period. The retailer is expected to settle the account at a time before the end of the inventory cycle time because the payable interest rate is generally higher than the earned interest rate. A model for optimal cycle and payment times is developed here for a retailer in a deteriorating-item inventory situation where a supplier allows a specified credit period to the retailer for payment without penalty. Under these conditions, this supplier-and-retailer system is modelled as a cost minimization problem to determine the optimal payment time under various system parameters. An iterative search procedure is applied to solve the problem, and the overall findings indicate that the retailer always has an option to pay after the permissible credit period depending on unit purchase and selling price, the deterioration rate of the products and the interest rate.     

On the dynamics of closed-loop supply chains under remanufacturing lead time variability

Remanufacturing practices in closed-loop supply chains (CLSCs) are often characterised by highly variable lead times due to the uncertain quality of returns. However, the impact of such variability on the dynamic benefits derived from adopting circular economy models remains largely unknown in the closed-loop literature. To fill the gap, this work analyses the Bullwhip and inventory performance of a multi-echelon CLSC with variable remanufacturing lead times under different scenarios of return rate and information transparency in the remanufacturing process. Our results reveal that ignoring such variability generally leads to an overestimation of the dynamic performance of CLSCs. We observe that enabling information transparency generally reduces order and inventory variability, but it may have negative effects on average inventory if the duration of the remanufacturing process is highly variable. Our findings result in useful and innovative recommendations for companies wishing to mitigate the negative consequences of lead time variability in CLSCs.     

Cognitive antecedents of business models: Exploring the link between attention and business model design over time

A firm's ability to conceive performance-enhancing business models (BMs) has become a cornerstone of competitive advantage. There is consensus that external triggers spur such BM change, but the literature has remained silent on the role of internal and cognitive antecedents such as managerial attention. In our inductive case study of four corporate spin-offs, we find that top management teams (TMTs) with a specific set of attention patterns are more likely to develop performance-enhancing BM designs. However, our findings provide evidence that specific attention foci are not sufficient to enhance particular BM designs, as it is also a matter of the intensity of attention. We further find that, over time, TMTs attention patterns shift and cause changes in BM designs. The emergent theoretical framework highlights that attention is an antecedent in explaining BM designs.     

Discrete models/continuous models

Continuous approximations are useful in formulating models that humans can comprehend. Discrete approximations are useful in formulating models that computers can “comprehend”. Applications of discrete and continuous approximations are illustrated with examples.