具有违约风险和交易费的房产期权定价

房价涨幅过快过高在中国房产市场已经是一个不容回避的问题.房产期权作为一种平衡买卖双方利益进行风险管理的有效工具应运而生.在Black-Scholes定价模型的基础上,考虑违约风险和交易费用这两个影响房产期权定价的重要因素,采用未定权益思想方法和△-对冲技巧建立了房产期权的定价模型,然后对模型进行求解,获得相应的数学公式,为考虑具有违约风险和交易费用影响下房产期权进行定价.     

具有违约观察期公司债券的定价

借助于美国破产保护法第十一章,违约公司获得-个额外的违约观察期过程,通过纳什均衡原理对股东和债权人的利益进行重新分配,利用巴黎型期权的定价思想来刻画具有这种违约观察期过程的股票与公司债券的定价模型,并从股东权益最大化,把股票的定价模型归结为-个自由边界问题,进而通过偏微分方程方法(PDE)推出股票与公司偾券价格的闭合表达式和最佳违约边界解的显式表达式;同时文章还对公司的最优杠杆,清算概率和信用利差进行讨论.     

LCDS pricing under structural frameworks

文中考虑贷款违约互换(LCDS)的定价模型.影响定价的两个主要因素早偿和违约分别用引入早偿强度和结构化方法来刻画.模型可转换为二维偏微分方程的定解问题,通过降维求其解给出了LCDS的保费的定价公式,并在此基础上给出数值算例.     

连续时间首达目标模型（Ⅰ）：折扣矩最优模型

1.引言 连续时间首达目标模型有广泛的实际背景,它可应用于可靠性系统的优化问题,排队系统的优化控制问题,自动控制中的决策优化问题,等等。我们准备研究下列几个模型: Ⅰ,折扣矩最优模型; Ⅱ,考虑工作寿命的最优模型; Ⅲ,首达时间依分布最优模型。     

考虑绿色等级和递送时间的双渠道绿色供应链

考虑了双渠道绿色供应链的定价决策问题.在集中式、分散式和协调合同条件下分别建立了双渠道绿色供应链的最优定价模型,给出了零售商和供应商的最优定价策略.研究表明,引入利润共享合同后零售商和供应商都会比在分散式决策下获得更多的利润.最后通过数值算例对不同条件下的模型进行了比较.     

基于无套利模型的人民币利率互换定价

基于两种代表性无套利模型——Black-Derman-Toy(BDT)和Hull-White模型,构建考虑单向违约风险的人民币利率互换定价模型。运用这两种定价模型对1年期3MSHIBOR-IRS进行定价,对两种定价模型的定价结果进行敏感性分析。结果表明,两种定价模型表现出定价偏离的一致性,基于BDT模型比基于Hull-White模型的定价结果与报价的差距更小。     

不同支付方式下的多模式项目支付进度问题研究

本文首先明确了研究的假设条件并对多模式项目支付进度问题（MPPSP）进行了界定;随后从承包商和业主两个角度构建了MPPSP的基本优化模型;鉴于支付方式的不同,将基本优化模型扩展为基于进展、基于时间和基于费用的MPPSP优化模型;最后,通过对一个算例的计算分析,讨论了支付方式对最优支付进度安排及合同双方收益的影响.     

CIR利率模型中基于对数效用的投资组合最优化问题

本文研究了CIR 利率模型中基于对数效用的最优长期投资问题和无限时间域上的最优折算消费问题. 通过求解相关的动态规划方程, 获得了这两个最优化问题的最优策略及值函数的明确表现形式.     

最优组合预测模型的构建及其应用研究

由于证券价格是随机游走的,在证券定价研究中RBF神经网络模型、灰色GM（1,1）模型、ARIMA模型不具备时效性,通过对上述三个模型进行综合分析,结合三者中有用的信息集合,构建一个最优组合预测模型．在此基础上选取了深发展A在2007年全年的收盘价作为研究样本对这四个模型进行实证研究,研究结果发现,最优组合预测方法对证券价格进行预测具有很好的预测精度和很高的可靠性．     

相依风险模型下具有延迟和违约风险的鲁棒最优投资和再保险策略（英文）

本文研究了在风险相依模型下具有延迟和违约风险的鲁棒最优投资再保险策略.假设模糊厌恶型保险人的财富过程有两类相依的保险业务并且余额可以投资于无风险资产、可违约债券和价格过程遵循Heston模型的风险资产.利用动态规划原则,我们分别建立了违约后和违约前的鲁棒HJB方程.另外,通过最大化终端财富的期望指数效用,我们得到了最优投资和再保险策略以及相应的值函数.最后,通过一些数值例子说明了某些模型参数对鲁棒最优策略的影响.     

Event risk, contingent claims and the temporal resolution of uncertainty

We study the pricing and hedging of contingent claims that are subject to Event Risk which we define as rare and unpredictable events whose occurrence may be correlated to, but cannot be hedged perfectly with standard marketed instruments. The super-replication costs of such event sensitive contingent claims (ESCC), in general, provide little guidance for the pricing of these claims. Instead, we study utility based prices under two scenarios of resolution of uncertainty for event risk: when the event is continuously monitored, or when it is revealed only at the payment date. In both cases, we transform the incomplete market optimal portfolio choice problem of an agent endowed with an ESCC into a complete market problem with a state and possibly path-dependent utility function. For negative exponential utility, we obtain an explicit representation of the utility based prices under both information resolution scenarios and this in turn leads us to a simple characterization of the early resolution premium. For constant relative risk aversion utility functions we propose a simple numerical scheme and study the impact of size of the position, wealth and expected return on these prices.     

A participatory multi-criteria approach for power generation and transmission planning

It is well-known that reinsurance can be an effective risk management solution for financial institutions such as the insurance companies. The optimal reinsurance solution depends on a number of factors including the criterion of optimization and the premium principle adopted by the reinsurer. In this paper, we analyze the Value-at-Risk based optimal risk management solution using reinsurance under a class of premium principles that is monotonic and piecewise. The monotonic piecewise premium principles include not only those which preserve stop-loss ordering, but also the piecewise premium principles which are monotonic and constructed by concatenating a series of premium principles. By adopting the monotonic piecewise premium principle, our proposed optimal reinsurance model has a number of advantages. In particular, our model has the flexibility of allowing the reinsurer to use different risk loading factors for a given premium principle or use entirely different premium principles depending on the layers of risk. Our proposed model can also analyze the optimal reinsurance strategy in the context of multiple reinsurers that may use different premium principles (as attributed to the difference in risk attitude and/or imperfect information). Furthermore, by artfully imposing certain constraints on the ceded loss functions, the resulting model can be used to capture the reinsurer’s willingness and/or capacity to accept risk or to control counterparty risk from the perspective of the insurer. Under some technical assumptions, we derive explicitly the optimal form of the reinsurance strategies in all the above cases. In particular, we show that a truncated stop-loss reinsurance treaty or a limited stop-loss reinsurance treaty can be optimal depending on the constraint imposed on the retained and/or ceded loss functions. Some numerical examples are provided to further compare and contrast our proposed models to the existing models.     

基于货到付款支付模式且考虑银行存贷的二级供应链Stackelberg定价决策

在货到付款支付模式下二级供应链定价决策中,供应链企业资金闲置时向银行存款或资金约束时向银行贷款(银行存贷)的行为是不可忽视的重要因素,如何构建基于货到付款支付模式且考虑银行存贷的二级供应链Stackelberg定价决策模型是需要关注的重要问题。在本文中,首先给出了市场需求函数;然后,基于货到付款支付模式,针对制造商资金或零售商资金约束情形,分别构建针对不同供应链权力结构的定价决策模型;进一步地,通过模型求解确定了不同情形下不同权力结构的制造商与零售商的最优策略,并分析了模型参数对最优策略的影响;最后,针对不同资金约束情形与不同权力结构的最优策略以及银行利率对最优策略及利润影响,给出了对比分析。研究表明三种银行利率均会影响最优策略,且资金约束对象差异的影响明显。     

Optimal XL-insurance under Wasserstein-type ambiguity

We study the problem of optimal insurance contract design for risk management under a budget constraint. The contract holder takes into consideration that the loss distribution is not entirely known and therefore faces an ambiguity problem. For a given set of models, we formulate a minimax optimization problem of finding an optimal insurance contract that minimizes the distortion risk functional of the retained loss with premium limitation. We demonstrate that under the average value-at-risk measure, the entrance-excess of loss contracts are optimal under ambiguity, and we solve the distributionally robust optimal contract-design problem. It is assumed that the insurance premium is calculated according to a given baseline loss distribution and that the ambiguity set of possible distributions forms a neighborhood of the baseline distribution. To this end, we introduce a contorted Wasserstein distance. This distance is finer in the tails of the distributions compared to the usual Wasserstein distance.     

Equilibruim approach of asset pricing under Lévy process

This work considers the equilibrium approach of asset pricing for Lévy process. It derives the equity premium and pricing kernel analytically for the stock price process, obtains an equilibrium option pricing formula, and explains some empirical evidence such as the negative variance risk premium, implied volatility smirk, and negative skewness risk premium by comparing the physical and risk-neutral distributions of the log return. Different from most of the current studies in equilibrium pricing under jump diffusion models, this work models the underlying asset price as the exponential of a Lévy process and thus allows nearly an arbitrage distribution of the jump component.     

Optimality of general reinsurance contracts under CTE risk measure

By formulating a constrained optimization model, we address the problem of optimal reinsurance design using the criterion of minimizing the conditional tail expectation (CTE) risk measure of the insurer’s total risk. For completeness, we analyze the optimal reinsurance model under both binding and unbinding reinsurance premium constraints. By resorting to the Lagrangian approach based on the concept of directional derivative, explicit and analytical optimal solutions are obtained in each case under some mild conditions. We show that pure stop-loss ceded loss function is always optimal. More interestingly, we demonstrate that ceded loss functions, that are not always non-decreasing, could be optimal. We also show that, in some cases, it is optimal to exhaust the entire reinsurance premium budget to determine the optimal reinsurance, while in other cases, it is rational to spend less than the prescribed reinsurance premium budget.     

Optimal access pricing for natural monopoly networks when costs are sunk and revenues are uncertain

This paper studies optimal access pricing for natural monopoly networks with large sunk costs and uncertain revenues. Using techniques from the option pricing literature, we show that the optimal access price corresponds to a risk-free form of the Efficiency Component Pricing Rule (ECPR), that is, where the opportunity cost is based on the risk free rate of return. We also show that at levels of revenue above the optimal level that triggers entry, the entrant should pay a premium above risk-free ECPR that rewards the incumbent for relinquishing his rights to the risky cash flows at the higher revenue level.     

Pareto-optimal insurance contracts with premium budget and minimum charge constraints

In view of the fact that minimum charge and premium budget constraints are natural economic considerations in any risk-transfer between the insurance buyer and seller, this paper revisits the optimal insurance contract design problem in terms of Pareto optimality with imposing these practical constraints. Pareto optimal insurance contracts, with indemnity schedule and premium payment, are solved in the cases when the risk preferences of the buyer and seller are given by Value-at-Risk or Tail Value-at-Risk. The effect of our constraints and the relative bargaining powers of the buyer and seller on the Pareto optimal insurance contracts are highlighted. Numerical experiments are employed to further examine these effects for some given risk preferences.     

从合成担保债务契约市场报价反求期望损失

研究通过CDO市场报价反求、校验期望损失的方法.在CDO风险中性定价的基础上建立介绍了通过市场报价反求期望损失的两个模型.比较了两种模型的优缺点.然后讨论了定价公式中不同的参数对保费的影响,并给出了模型的两个应用:求标的资产的违约分布以及计算非标准层的定价.     

Optimal investment and premium control in a nonlinear diffusion model

This paper considers the optimal investment and premium control problem in a diffusion approximation to a non-homogeneous compound Poisson process. In the nonlinear diffusion model, it is assumed that there is an unspecified monotone function describing the relationship between the safety loading of premium and the time-varying claim arrival rate. Hence, in addition to the investment control, the premium rate can be served as a control variable in the optimization problem. Specifically, the problem is investigated in two cases: (i) maximizing the expected utility of terminal wealth, and (ii) minimizing the probability of ruin respectively. In both cases, some properties of the value functions are derived, and closed-form expressions for the optimal policies and the value functions are obtained. The results show that the optimal investment policy and the optimal premium control policy are dependent on each other. Most interestingly, as an example, we show that the nonlinear diffusion model reduces to a diffusion model with a quadratic drift coefficient when the function associated with the premium rate and the claim arrival rate takes a special form. This example shows that the model of study represents a class of nonlinear stochastic control risk model.