Bilevel optimization applied to strategic pricing in competitive electricity markets

In this paper, we present a bilevel programming formulation for the problem of strategic bidding under uncertainty in a wholesale energy market (WEM), where the economic remuneration of each generator depends on the ability of its own management to submit price and quantity bids. The leader of the bilevel problem consists of one among a group of competing generators and the follower is the electric system operator. The capability of the agent represented by the leader to affect the market price is considered by the model. We propose two solution approaches for this non-convex problem. The first one is a heuristic procedure whose efficiency is confirmed through comparisons with the optimal solutions for some instances of the problem. These optimal solutions are obtained by the second approach proposed, which consists of a mixed integer reformulation of the bilevel model. The heuristic proposed is also compared to standard solvers for nonlinearly constrained optimization problems. The application of the procedures is illustrated in case studies with configurations derived from the Brazilian power system.     

Managing uncertainty in call centres using Poisson mixtures

We model a call centre as a queueing model with Poisson arrivals having an unknown varying arrival rate. We show how to compute prediction intervals for the arrival rate, and use the Erlang formula for the waiting time to compute the consequences for the occupancy level of the call centre. We compare it to the current practice of using a point estimate of the arrival rate (assumed constant) as forecast. Copyright © 2001 John Wiley & Sons, Ltd.     

Evaluation of insurance products with guarantee in incomplete markets

Life insurance products are usually equipped with minimum guarantee and bonus provision options. The pricing of such claims is of vital importance for the insurance industry. Risk management, strategic asset allocation, and product design depend on the correct evaluation of the written options. Also regulators are interested in such issues since they have to be aware of the possible scenarios that the overall industry will face. Pricing techniques based on the Black & Scholes paradigm are often used, however, the hypotheses underneath this model are rarely met.To overcome Black & Scholes limitations, we develop a stochastic programming model to determine the fair price of the minimum guarantee and bonus provision options. We show that such a model covers the most relevant sources of incompleteness accounted in the financial and insurance literature. We provide extensive empirical analyses to highlight the effect of incompleteness on the fair value of the option, and show how the whole framework can be used as a valuable normative tool for insurance companies and regulators.     

Style goods pricing with demand learning

For many industries (e.g., apparel retailing) managing demand through price adjustments is often the only tool left to companies once the replenishment decisions are made. A significant amount of uncertainty about the magnitude and price sensitivity of demand can be resolved using the early sales information. In this study, a Bayesian model is developed to summarize sales information and pricing history in an efficient way. This model is incorporated into a periodic pricing model to optimize revenues for a given stock of items over a finite horizon. A computational study is carried out in order to find out the circumstances under which learning is most beneficial. The model is extended to allow for replenishments within the season, in order to understand global sourcing decisions made by apparel retailers. Some of the findings are empirically validated using data from U.S. apparel industry.     

带缓冲器的巴黎地铁定价策略

本在巴黎地铁定价(PMP(Paris Metro Pricing))的基础上研究了一种带有缓冲器的巴黎地铁定价策略。同样将网络分成几个逻辑上独立的不同部分，每一个部分制定不同的价格，各部分仅在价格上有区别。但是额外增加一个适合“中性消费”需求的缓冲器，使得“中性消费”可以先向缓冲器提交服务请求，而后由ISP网络提供商根据各部分的实际负载状况将其分配到合适的服务节点。最后通过仿真说明与巴黎地铁相比，带有缓冲器的巴黎地铁定价策略在网络拥塞控制与网络资源分配等方面有更高的效率。     

基于利率市场化的银行贷款竞争导向定价策略研究

本文着重对两个银行之间竞争导向定价策略博弈行为进行了分析，认为在利率管制条件下，银行难以运用利率杠杆在信贷市场进行有效竞争；利率市场化之后，监管者不再对利率进行约束，银行信贷竞争的广度和深度都会随之加大。因此价格竞争将是银行信贷市场竞争的常态。     

电子政务系统中面向公众的个性化信息服务模型

电子政务作为Internet的主要应用领域，已受到世界各国的普遍关注。面对公众各种服务需求日趋个性化，如何打破政府职能机构的条块分割，构建一个一体化的虚拟政府，集成各类信息资源，为公众提供“一站式”的、个性化的服务，是当前电子政务理论和实践的热点课题。本文首先提出一个面向公众的“一站式”服务总体框架；其次，将个性化信息服务的概念引入到电子政务系统中，构建一个个性化信息服务模型；最后，运用数据挖掘技术对模型中的关键技术加以实现。     

Dependence properties and comparison results for Lévy processes

In this paper we investigate dependence properties and comparison results for multidimensional Lévy processes. In particular we address the questions, whether or not dependence properties and orderings of the copulas of the distributions of a Lévy process can be characterized by corresponding properties of the Lévy copula, a concept which has been introduced recently in Cont and Tankov (Financial modelling with jump processes. Chapman & Hall/CRC, Boca Raton, 2004) and Kallsen and Tankov (J Multivariate Anal 97:1551–1572, 2006). It turns out that association, positive orthant dependence and positive supermodular dependence of Lévy processes can be characterized in terms of the Lévy measure as well as in terms of the Lévy copula. As far as comparisons of Lévy processes are concerned we consider the supermodular and the concordance order and characterize them by orders of the Lévy measures and by orders of the Lévy copulas, respectively. An example is given that the Lévy copula does not determine dependence concepts like multivariate total positivity of order 2 or conditionally increasing in sequence. Besides these general results we specialize our findings for subfamilies of Lévy processes. The last section contains some applications in finance and insurance like comparison statements for ruin times, ruin probabilities and option prices which extends the current literature. Anja Blatter was supported by the Deutsche Forschungsgemeinschaft (DFG).     

Portfolio Selection Problem with Minimax Type Risk Function

The investor's preference in risk estimation of portfolio selection problems is important as it influences investment strategies. In this paper a minimax risk criterion is considered. Specifically, the investor aims to restrict the standard deviation for each of the available stocks. The corresponding portfolio optimization problem is formulated as a linear program. Hence it can be implemented easily. A capital asset pricing model between the market portfolio and each individual return for this model is established using nonsmooth optimization methods. Some numerical examples are given to illustrate our approach for the risk estimation.     

城市交通管理中的出租车规划模型

最佳数量的确定和价格的制定是城市出租车规划中的两个核心问题.对影响出行强度的市区人口和建成区面积分析建立了出行总量预测模型,再通过分析出租车最佳数量与出租车运营里程的关系,得出出租车最佳数量的预测模型.在出租车最佳数量模型的基础上,分析出租车数量的差异和差异产生的原因,给出了出租车定价判断模型,为出租车定价机制的调整指明了方向.最后以长沙市为例进行了实证分析.