模糊环境下带交易费用的权证定价模型——纪念李国平院士吴新谋教授诞辰100周年

该文综合考虑我国证券市场中广泛存在的隐性交易费用, 建立了模糊环境下带交易费用的权证定价模型. 在假设交易费用率为三角型模糊数的前提下导出了新的权证价格区间, 并通过引入模糊期望的概念, 将区间数转化为与投资者主观判断无关的准确数. 基于此模型, 对模型中三角型模糊数的关键参数 进行了灵敏度分析和投资策略分析.     

股指期货冲击成本测算与实证研究

本文首先对国外测算冲击成本常用的一种方法基于中国市场的实际进行了改进,并将其运用到沪深300股指期货合约中,对永久冲击成本和暂时冲击成本分别建模并运用高频交易数据加以测算模拟和实证分析,对线性和非线性两种形式的冲击函数模拟了投资者冲击成本最小的交易策略。本文的结论可直接用于投资者交易冲击成本估算、以及程序化和算法交易研究中的冲击成本模型输入。从模拟结果来看,中国市场的冲击成本显著高于更加发达成熟的美国市场,侧面显示了中国市场的流动性和有效性要弱于美国市场。     

内部交易行为对股票价格影响机制研究

上市公司的内部人或者机构投资者通常拥有比其他投资者更多的信息,诸多实证研究已经证明内部交易者能够利用私有信息在市场中获利.我国自2014年起开始在新三板市场中实施做市商制度,在这一大背景下,主要对内部交易者的交易行为进行了理论预测性研究.在经典的信息模型框架下,通过讨论股票价格的鞅性,建立了一种带有预防对冲策略控制系数的风险厌恶模型.模型表明内部交易者可以充分利用私有信息对做市商的定价进行预测,并且有针对性的选择交易策略以获利.     

基于流动性约束和价格趋势的最优交易策略

股票市场中当交易规模较大时,投资者不仅要预判未来的股票价格趋势从而降低风险成本,也要考虑大额交易指令对市场冲击的成本.在投资者预判股票未来价格趋势的同时,考虑交易量的线性价格冲击,建立一个控制最小交易成本的策略模型,采用随机动态规划方法得出总体执行成本最小的交易策略解析解,进一步利用数值算例对最优交易策略进行了比较静态分析.     

模糊环境下带交易费用的权证定价模型

该文综合考虑我国证券市场中广泛存在的隐性交易费用,建立了模糊环境下带交易费用的权证定价模型.在假设交易费用率为三角型模糊数的前提下导出了新的权证价格区间,并通过引入模糊期望的概念,将区间数转化为与投资者主观判断无关的准确数.基于此模型,对模型中三角型模糊数的关键参数进行了灵敏度分析和投资策略分析.     

搜索成本对B2B交易的影响研究——基于上游企业主导搜索的分析

搜索交易伙伴是企业开展B2B交易流程中的首要一环。当下,信息通讯技术的扩散简化了企业搜索交易伙伴的程序,搜索成本得到极大降低,交易效率得以极大提升。本文考虑B2B交易由上游企业主导搜索实现的情况下,搜索成本降低对B2B交易规模及产业竞争的影响。企业搜索成本降低对企业的交易行为将产生两种效应:进入效应和匹配效应。进入效应促使更多企业进入市场参与交易;匹配效应促使企业持续搜寻最优的交易伙伴。理论分析结果与一般直观认识相悖,具体而言,若交易由上游企业主导完成,两种效应叠加导致B2B交易并非总是随着搜索成本的降低而持续增长,而是呈现出增中有降的态势;同时,搜索成本的降低对主导搜索企业所在产业发展有利亦有弊,并不必然导致一个竞争更加剧烈的产业格局。     

应用微模拟方法分析交易费用对股票市场影响的研究

基于对中国股票市场的连续竞价交易机制和投资者构成特征的分析,本文构建了一个人工模拟订单驱动股票市场模型。模型能够得出一系列与实际股票市场一致的典型事实,如收益率分布的胖尾特征以及波动率的聚集等。通过在模拟实验中设定不同的交易费用约束,分析了不同程度的交易费用约束对股票市场的影响。结果表明,交易费用的增加会导致股票换手率的大幅下降;由于流动性不足,提高交易费用水平并不一定能够达到降低市场波动的目的。     

大额交易的生存分析与微观市场状态变迁

本文将运筹学中的排队论思想和数量统计学中的生存分析方法引入到金融高频数据分析中，从市场微观结构角度研究了价格过程中大额交易的发生与市场状态变量之间的相互作用：一方面大额交易对价格具有明显的拉动作用，另一方面报价变化、流动性深度和成本以及交易特征等市场因素也影响着大额交易的发生。本文以国有股减持信息人市为例，分析了大额交易的生存参数变化与市场状态变迁之问的关系。     

碳减排外包下的契约优化与选择研究

在政府碳配额、碳交易市场机制和消费者低碳偏好背景下,研究了制造商与低碳服务提供商合作下的碳减排外包问题。对技术交易型契约和合作共享型契约两种契约进行了优化,分别得到了两种契约下的最优决策和契约可达成条件,并进一步分析了制造商和低碳服务提供商对两种契约的偏好,最后利用转移支付的方式对契约偏好冲突问题进行了协调。研究结果表明,单位减排成本和碳排放权市场价格均是影响技术交易型契约和合作共享型契约可行性的关键因素;当单位最小碳排放量、单位减排成本和碳排放权市场价格同时满足一定条件时,两种契约可同时达成;制造商总是偏好技术交易型契约,但低碳服务提供商对于契约类型的偏好并不是确定的;利用转移支付协调的方式可以解决合作双方的契约偏好冲突问题,并使得双方最终达成技术交易型契约。     

中国证券市场知情交易概率的动态马尔科夫状态转移模型研究

对指令驱动市场知情交易的研究是近年来的热点问题。常用的EKOP模型存在一些缺陷,本文放宽了EKOP模型关于日内信息均匀释放以及交易者行为独立性的假设,用动态的马尔科夫状态转移模型对该模型进行了改进,并检验了改进后的知情交易概率模型在中国证券市场的适用性。通过模拟数据以及对中国证券市场交易数据的实证研究发现动态的马尔科夫状态转移模型克服了EKOP模型受买卖方数据影响而产生的系统偏误,估计的知情交易概率更符合事后检验。     

Integrating link-based discrete credit charging scheme into discrete network design problem

In this paper, we present an optimization model for integrating link-based discrete credit charging scheme into the discrete network design problem, to improve the transport performance from the perspectives of both transport network planning and travel demand management. The proposed model is a mixed-integer nonlinear bilevel programming problem, which includes an upper level problem for the transport authority and a lower level problem for the network users. The lower level sub-model is the traffic network user equilibrium (UE) formulation for a given network design strategy determined by the upper level problem. The network user at the lower level tries to minimize his/her own generalized travel cost (including both the travel time and the value of the credit charged for using the link) by choosing his/her route. While the transport authority at the upper level tries to find the optimal number of lanes and credit charging level with their locations to minimize the total system travel time (or maximize the transportation system performance). A genetic algorithm is used to solve the proposed mixed-integer nonlinear bilevel programming problem. Numerical experiments show the efficiency of the proposed model for traffic congestion mitigation, reveal that interaction effects across the tradable credit scheme and the discrete network design problem which amplify their individual effects. Moreover, the integrated model can achieve better performance than the sequential decision problems.     

Sensitivity analysis for the asymmetric network equilibrium problem

We consider the asymmetric continuous traffic equilibrium network model with fixed demands where the travel cost on each link of the transportation network may depend on the flow on this as well as other links of the network and we perform stability and sensitivity analysis. Assuming that the travel cost functions are monotone we first show that the traffic equlibrium pattern depends continuously upon the assigned travel demands and travel cost functions. We then focus on the delicate question of predicting the direction of the change in the traffic pattern and the incurred travel costs resulting from changes in the travel cost functions and travel demands and attempt to elucidate certain counter intuitive phenomena such as ‘Braess' paradox’. Our analysis depends crucially on the fact that the governing equilibrium conditions can be formulated as a variational inequality. This work was supported by the Program of University Research, U.S. Department of Transportation (Project number DTRS 5680-C-00007).     

多方式弹性需求下公交定价双层规划模型

为描述多方式城市交通网络下公交定价与出行选择行为的相互作用与影响,将出行方式选择与路径选择涵盖于同一网络,建立了上层模型分别以企业利润最大化、乘客出行成本最小化和社会福利最大化为目标函数,下层模型为多方式弹性需求随机用户配流模型的公交定价双层规划模型。运用改进遗传算法对模型整体进行求解,下层模型采用综合对角化算法和MSA算法的组合求解算法。最后,设计了一个算例以说明模型应用。结果表明:运用双层规划模型所确定的公交票价较传统静态票价可使政府、企业及出行者三方都获得更高收益,且上层模型以社会福利最大化为目标函数能代表社会群体中多数人利益,优化效果最为理想。     

基于客户信用度的物流配送车辆路径问题研究

针对当前城市物流配送过程中普遍存在的客户中途取消订单、无故退换货等交易违约问题,引入客户信用度的测度方法。根据客户历史交易违约数据计算客户信用值,并转化求解客户信用度,构建了包含车辆配送成本、租赁成本以及违反时间窗惩罚成本的配送路径优化模型。设计了一种遗传(GA)-禁忌搜索(TS)混合算法进行模型求解,在算法过程中应用精英保留策略进行循环迭代寻优。结合重庆某外卖物流配送网络的实例数据,验证了模型和算法的有效性和可行性。实验结果给出了不同服务策略下的物流配送调度方案,并进行了基于客户信用度的客户配送服务序列调整比较和敏感度分析。研究表明客户信用等级的合理划分可以有效降低物流配送成本和提高客户服务水平。     

Novel travel cost functions based on morning peak commuting equilibrium

This paper derives two novel travel cost functions by formulating a morning commuting equilibrium model that incorporates traffic congestion based on fundamental traffic flow diagram. The travel cost functions have components to represent traversal cost, waiting queuing costs and early arrival penalty. It is found that the equilibrium travel cost is a concave function of the total demand in the uncongested regime but an increasing linear function of the total demand in the congested regime.     

Using fuzzy integral for evaluating subjectively perceived travel costs in a traffic assignment model

A good traffic assignment model can be a powerful tool to describe the characteristics of traffic behavior in a road network. The traffic assignment results often play an important role in transportation planning, e.g., an optimal and economical network design. Many traditional traffic assignment models rely heavily on the travel cost function established by Wardrop’s principles; however, the Wardrop’s travel cost function has been proven to be weak for explaining the uncertainty and interactivity of traffic among links. This study tries to construct a traffic assignment model that is different from Wardrop’s in many aspects. First, it considers the cross-effect among the links. Second, a fuzzy travel cost function is established based on the possibility concept instead of precise calculation of traffic volumes. Third, the techniques of fuzzy measure and fuzzy integral are applied to calculate the subjectively perceived travel costs during traffic assignment. Furthermore, in order to validate our model, a detailed network with 22 nodes and 36 links is used to illustrate it. Study results show that our model explains more interactivity and uncertainty of traffic among links when compared with the traditional model of Wardrop’s.     

基于双层规划的高速公路收费费率优化模型

在全国联网收费的背景下,从动态收费的角度考虑,建立了双层规划模型,上层规划中将路网管理者作为领导者,以高速公路收费效益最大化为目标函数,同时考虑道路运营管理方的合理收益和养护成本支出情况,下层规划则以用户出行效用最大化为目标,充分考虑了道路使用者的道路选择差异性及道路拥堵对交通分布的影响,建立随机用户均衡模型.最后结合某地区AB地高速公路实际情况进行分析,采用了遗传模拟退火算法验证了模型的实用性,并与其他的算法对比,验证了算法的有效性。研究表明:优化模型可以有效提高高速公路的收费效益和用户的出行效用,可以分散高峰时的交通压力,提升高速公路的通行效率.     

Sensitivity Analysis Based Method for Optimal Road Network Pricing

Road pricing is an important economic measure for optimal management of transportation networks. The optimization objectives can be the total travel time or total cost incurred by all the travelers, or some other environmental objective such as minimum emission of dioxide, an so on. Suppose a certain toll is posed on some link on the network, this will give an impact on flows over the whole network and brings about a new equilibrium state. An equilibrium state is a state of traffic network at which no traveler could decrease the perceived travel cost by unilaterally changing the route. The aim of the toll setting is to achieve such an equilibrium state that a certain objective function is optimized. The problem can be formulated as a mathematical program with equilibrium constraints (MPEC). A key step for solving such a MPEC problem is the sensitivity analysis of traffic flows with respect to the change of link characteristics such as the toll prices. In this paper a sensitivity analysis based method is proposed for solving optimal road pricing problems.     

Average shadow price and equilibrium price: A case study of tradable pollution permit markets

Shadow prices indicate implicit values of limited resources at the margin and provide important information in decision making for resource management. In continuous economic models, shadow prices associated with demand-supply balance constraints represent consumers’ willingness to pay and producers’ marginal cost, hence they correspond to market equilibrium prices. As well known, however, marginal analysis fails in the case of discrete optimization, such as mixed integer programming. An alternative concept has been introduced in the literature to measure the value of an extra unit of a limited resource in such cases. This concept is based on average rather than marginal values, thus called the average shadow price, and interpreted in the same way as conventional shadow prices. Whether average shadow prices in a discrete economic model can serve as market equilibrium prices has not been addressed in the related literature. The present paper addresses this issue in an empirical setting. Using a tradable pollution permit market as an example, where firms’ YES/NO type technology adoption decisions are represented by binary variables, we show that the average shadow price of tradable permits can be interpreted as the equilibrium price only when certain conditions related to the cost structure and emission levels hold. On the other hand, we show that an iterative procedure based on individual firms’ cost minimizing behavior presents a better approach for finding a price that can eliminate or reduce the gap between demand and supply of permits in the market.     

考虑路网可靠性和空间公平性的次优拥挤收费模型

根据随机路网环境下出行者规避风险的路径选择行为,提出了一种考虑路网可靠性和空间公平性的次优拥挤收费双层规划模型。其中,上层模型以具有空间公平性约束条件下最大化路网的社会福利为目标,下层模型是实施拥挤收费条件下考虑行程时间可靠性的弹性需求用户平衡模型。鉴于双层规划模型的复杂性,设计了基于遗传算法和FrankWolfe算法的组合式算法来求解提出的模型。算例结果表明:考虑行程时间可靠性的次优拥挤收费会产生不同于传统次优拥挤收费的平衡流量分布模式,表明出行者的路径选择行为对拥挤收费结果会产生直接影响;此外,算例结果还说明遗传算法对参数设置具有很强的鲁棒性。