Homogeneous Customers Renege from Invisible Queues at Random Times under Deteriorating Waiting Conditions

We consider a memoryless first-come first-served queue in which customers' waiting costs are increasing and convex with time. Hence, customers may opt to renege if service has not commenced after waiting for some time. We assume a homogeneous population of customers and we look for their symmetric Nash equilibrium reneging strategy. Besides the model parameters, customers are aware only, if they are in service or not, and they recall for how long they are have been waiting. They are informed of nothing else. We show that under some assumptions on customers' utility function, Nash equilibrium prescribes reneging after random times. We give a closed form expression for the resulting distribution. In particular, its support is an interval (in which it has a density) and it has at most two atoms (at the edges of the interval). Moreover, this equilibrium is unique. Finally, we indicate a case in which Nash equilibrium prescribes a deterministic reneging time.     

Unified Model for Generation Complex Networks with Utility Preferential Attachment

In this paper, based on the utility preferential attachment, we propose a new unified model to generate different network topologies such as scale-free, small-world and random networks. Moreover, a new network structure named super scale network is found, which has monopoly characteristic in our simulation experiments. Finally, the characteristics of this new network are given.     

On twice differentiable direct and indirect utility functions and the monotonicity of the demand

This article investigates the relationships between the Hessians of the direct and indirect utility function and the Jacobian of the demand correspondence. The monotonicity of the demand is analysed thanks to the convexity indices of the function and the monotonicity index of the demand.     

Valuing risky income streams in incomplete markets

A model for pricing and hedging in incomplete markets is proposed. This model is derived from expected utility theory, and a connection with the traditional no‐arbitrage framework is noted. It is shown that the CGM model can be implemented to value risky assets in incomplete markets.     

Worst portfolios for dynamic monetary utility processes

We study the worst portfolios for a class of law invariant dynamic monetary utility functions with domain in a class of stochastic processes. The concept of comonotonicity is introduced for these processes in order to prove the existence of worst portfolios. Using robust representations of monetary utility function processes in discrete time, a relation between the worst portfolios at different periods of time is presented. Finally, we study conditions to achieve the maximum in the representation theorems for concave monetary utility functions that are continuous for bounded decreasing sequences.     

Preserving the Rothschild–Stiglitz type increase in risk with background risk: A characterization

In order to generalize previous results by Li et al. (2016), Guo et al. (2016) extended the definition of the Rothschild–Stiglitz type of increase in risk to a background risk framework. They provided several sufficient conditions for such a ranking to hold, involving expectation dependence concepts. In this short note, the corresponding characterizations are established, based on the bivariate higher-degree increasing concave orders introduced by Denuit et al. (1999).     

The risk transfer of non-tradable risks under model uncertainty

In the context of model uncertainty, we study the optimal design and the pricing of financial instruments aiming to hedge some of non-tradable risks. For the existence of model uncertainty, the preference can be represented by the robust expected utility (also called maxmin expected utility) which can be put in the framework of sublinear expectation. The problem of maximizing the issuer’s robust expected utility under the constraint imposed by the buyer can be transformed to the problem of minimizing the issuer’s convex measure under the corresponding constraint. And here the convex measure measures not only the risks but also the model uncertainties.     

指数保费准则下的最优投资和比例再保险

该文研究了保险公司的最优投资和比例再保险问题,其中假定保险公司的盈余过程为一个带扩散扰动的经典风险过程.假定再保险的保费按照指数保费原理来计算,这使得所研究的随机控制问题成为非线性的.该文同时考虑了最大化终端财富指数效用和最大化调节系数两类问题,并给出了最优值函数和相应的最优策略的解析表达.此外,该文还分析了再保险公司的风险厌恶和保险公司的不确定性参数对最优策略的影响.