均值-方差准则下的多期最优保险投资(英文)

近年来,最优保险投资问题吸引了越来越多的注意。一般这个问题是在连续时间框架下来研究的。本文针对这一问题建立离散时间的最优控制模型。应用动态规划原理求解模型对应的近似问题,得到了最优投资策略和投资有效边界的解析表达形式。本文得到的最优投资策略和投资有效边界均依赖于承保参数。通过数值例子分析了承保参数对最优投资策略和有效边界的影响。     

带扰动的随机保费模型的渐近最优投资

本文研究了一类具有随机投资回报的随机保费模型的最小破产概率的渐近性质.在假定常值投资策略的情形下,通过最小化调节系数,我们得到了与此调节系数相对应的最优的常值投资策略.最后我们证明当初始盈余趋向于无穷的时候,最优的投资策略趋向于这个常值策略.     

竞争条件下公司最优投资策略纳什均衡分析

大多数实物期权文献都只是研究一个公司在没有竞争条件下的最优决策,然而实际上竞争者的行为经常影响到公司的投资机会.通过建立投资概率是临界值的函数模型,根据期权博弈理论研究了在不确定条件和不同信息结构下,一个或多个公司的最优投资策略纳什均衡解,并用MATLAB语言对案例进行了仿真分析,画图说明了参数变化对投资策略的影响.     

基于通货膨胀和最低保障的DC养老金最优投资

主要研究了通货膨胀和最低保障下的DC养老金的最优投资问题。 首先, 应用伊藤公式得到通胀折现后真实股票价格的微分方程。 然后, 在DC养老金终端财富外部保障约束下, 引入欧式看涨期权, 考虑随机通胀环境下的退休时刻终端财富期望效用最大化问题, 应用鞅方法推导退休时刻以及退休前任意时刻DC养老金最优投资策略的显式解。 最后, 应用蒙特卡洛方法对结果进行数值分析, 分析最低保障对DC养老金最优投资策略的影响。     

基于CvaR的融入期权的投资组合模型

把期权作为一种投资对象融入到投资组合中,而不仅仅是作为风险对冲工具.用条件风险价值(CVaR)刻画组合风险,并求出最小化风险下的最优鲁棒投资组合策略.最后通过数值算例证明了模型的有效性,并得到融入期权后有效地提高了组合的收益,特别是当标的资产出现大的波动时,期权在组合中的表现更突出.     

非对称情形下R＆D竞争项目的策略性投资

在非对称情形下,考虑具有技术不确定和未来收益不确定的竞争研究与开发(R&D)项目的不可逆策略性投资.利用期权博弈理论和随机优化方法给出了高效研发公司(主导者)的最优投资阈值和最优投资规则的解析表达式,并证明了由于两公司的竞争使投资阈值下降.其次讨论了两公司的混合投资策略,并给出每个公司执行投资期权的概率和两公司同时执行投资期权的概率.在最后给出了数值模拟算例来说明该文结论的合理性.     

非对称情形下R & D竞争项目的策略性投资

在非对称情形下,考虑具有技术不确定和未来收益不确定的竞争研究与开发(R&;D)项目的不可逆策略性投资.利用期权博弈理论和随机优化方法给出了高效研发公司(主导者) 的最优投资阈值和最优投资规则的解析表达式,并证明了由于两公司的竞争使投资阈值下降.其次讨论了两公司的混合投资策略,并给出每个公司执行投资期权的概率和两公司同时执行投资期权的概率. 在最后给出了数值模拟算例来说明该文结论的合理性.     

双币种博弈期权

博弈期权是一种赋予期权出售方在期权有效期内任意时刻可以赎回合约权利的美式期权.在B-S框架下分析了双币种情形下的博弈期权定价行为,建立了双币种博弈期权的定价模型,分别讨论了敲定价以国内货币计价和国外货币计价下的博弈期权定价问题及其最优赎回策略,通过运用偏微分方程的方法得到了这两种情形下期权价格的表达式及其最优执行边界.最后通过数值模拟,分析了标的资产和汇率的波动水平以及汇率与标的资产的相关系数对期权的最优执行策略和违约金边界的影响.     

部分信息下期望消费效用最大的优化问题

研究了部分信息下期望消费效用最大的优化问题.利用凸分析理论,非线性滤波和Malliavin导数技术,得到了最优投资-消费策略和代价泛函.对于对数效用函数情形,给出了一个估算信息价值的公式,它是完全信息下和部分信息下所对应的最优代价泛函的差值.     

不完全市场下基于对数效用的动态投资组合

应用鞅方法研究不完全市场下的动态投资组合优化问题。首先,通过降低布朗运动的维数将不完全金融市场转化为完全金融市场,并在转化后的完全金融市场里应用鞅方法研究对数效用函数下的动态投资组合问题,得到了最优投资策略的显示表达式。然后,根据转化后的完全金融市场与原不完全金融市场之间的参数关系,得到原不完全金融市场下的最优投资策略。算例分析比较了不完全金融市场与转化后的完全金融市场下最优投资策略的变化趋势,并与幂效用、指数效用下最优投资策略的变化趋势做了比较。     

考虑即时采购价格的物流服务供应链优化

物流服务市场的不确定性会影响物流服务供应链的服务水平和收益。在考虑随机即时采购价格以及基础物流提供商在正常情况和应急情况下具有不同物流能力投资成本的情形下,引入期权机制研究不确定市场环境下物流服务供应链的优化决策,以提高物流服务供应链柔性和降低市场不确定性带来的风险。构建物流服务供应链的期权契约模型,采用Stackelberg博弈理论和优化算法分析和求得物流服务集成商的最优期权采购和即时采购策略,以及基础物流提供商的最优物流能力投资策略。结果表明即时采购价格将影响基础物流提供商和物流服务集成商的决策。最后通过数值分析研究即时采购价格的不确定程度对物流服务集成商和提供商的优化策略和利润的影响。     

Debt recapitalization and value in waiting to finance a project

This paper shows that an option to recapitalize with debt accelerates the exercise of a real option to start an irreversible project investment. The debt-recapitalization add-on, while not directly affecting project cash flows, influences the timing of the project start by offering an extra gain from tax savings less debt costs. This finding demonstrates that capital structure decisions are closely linked to project investment decisions, a deviation from the standard optimal investment rule of the real option theory.     

多种风险下研发项目投资决策博弈分析

研发项目代表了高新技术企业的核心竞争力,但是其投资和研发的过程所包含的多种风险可能会造成企业经济上的损失。为了保证竞争优势和收益最大化,企业投资前需要对项目的估值非常的精确,以便在竞争中做出最优投资决策。本文以市场中的两个竞争性企业为例,利用欧式复合期权理论与博弈论,量化了技术风险、商业风险和突发风险等不确定性,在经过了信息披露过程之后,分析了市场中企业自身和竞争者的投资决策,建立相应的研发项目投资决策数学模型,对企业的研发项目投资时机和决策收益进行评估,通过博弈得到纳什均衡下的企业最优投资决策。     

The impact of delaying an investment decision on R&D projects in real option game

In a research and development (R&D) investment, the cost and the project value of such an investment are usually uncertain, which thus increases its complexity. Correspondingly, the NPV (Net Present Value) rule fails to evaluate the value of this project exactly, because this method does not take into account the market uncertainty, irreversibility of investment and ability of delay entry. In this paper, we employ the real option theory to evaluate the project value of a R&D investment. Since the cost of a R&D investment is very high and the flow of the information is crowded, an investor cannot make an immediate decision every time. So, the proposed real option model is an exchange option. At the same time, combining the real option and the game theory, we can find the Nash equilibrium which is the optimal strategy. Moreover, we also study how the delayed time influences the price of the project investment and how the different delayed times effect the choice of the optimal strategies.     

Multi-resource investment strategies: Operational hedging under demand uncertainty

Consider a firm that markets multiple products, each manufactured using several resources representing various types of capital and labor, and a linear production technology. The firm faces uncertain product demand and has the option to dynamically readjust its resource investment levels, thereby changing the capacities of its linear manufacturing process. The cost to adjust a resource level either up or down is assumed to be linear. The model developed here explicitly incorporates both capacity investment decisions and production decisions, and is general enough to include reversible and irreversible investment. The product demand vectors for successive periods are assumed to be independent and identically distributed. The optimal investment strategy is determined with a multi-dimensional newsvendor model using demand distributions, a technology matrix, prices (product contribution margins), and marginal investment costs. Our analysis highlights an important conceptual distinction between deterministic and stochastic environments: the optimal investment strategy in our stochastic model typically involves some degree of capacity imbalance which can never be optimal when demand is known.     

含不动产项目的保险公司再保险-投资策略

站在保险公司管理者的角度, 考虑存在不动产项目投资机会时保险公司的再保险--投资策略问题. 假定保险公司可以投资于不动产项目、风险证券和无风险证券, 并通过比例再保险控制风险, 目标是最小化保险公司破产概率并求得相应最佳策略, 包括: 不动产项目投资时机、 再保险比例以及投资于风险证券的金额. 运用混合随机控制-最优停时方法, 得到最优值函数及最佳策略的显式解. 结果表明, 当且仅当其盈余资金多于某一水平(称为投资阈值)时保险公司投资于不动产项目. 进一步的数值算例分析表明: (a)~不动产项目投资的阈值主要受项目收益率影响而与投资金额无明显关系, 收益率越高则投资阈值越低; (b)~市场环境较好(牛市)时项目的投资阈值降低; 反之, 当市场环境较差(熊市)时投资阈值提高.     

Optimal production strategy under demand fluctuations: Technology versus capacity

This paper provides a comparative analysis of five possible production strategies for two kinds of flexibility investment, namely flexible technology and flexible capacity, under demand fluctuations. Each strategy is underpinned by a set of operations decisions on technology level, capacity amount, production quantity, and pricing. By evaluating each strategy, we show how market uncertainty, production cost structure, operations timing, and investment costing environment affect a firm’s strategic decisions. The results show that there is no sequential effect of the two flexibility investments. We also illustrate the different ways in which flexible technology and flexible capacity affect a firm’s profit under demand fluctuations. The results reveal that compared to no flexibility investment, flexible technology investment earns the same or a higher profit for a firm, whereas flexible capacity investment can be beneficial or harmful to a firm’s profit. Moreover, we prove that higher flexibility does not guarantee more profit. Depending on the situation, the optimal strategy can be any one of the five possible strategies. We also provide the optimality conditions for each strategy.     

在折现率大于零的情况下,具有完成时间和残值不确定性的R&D项目的投资策略

利用随机停时理论 ,考虑 R&D项目的连续投资策略 .在折现率大于零的情况下 ,给出了具有建设期和残值的不确定性的 R&D投资模型、放弃 R&D项目投资的临界值和最优决策规则 ,并讨论参数对临界值的影响 .也进一步验证了随机停时理论和实物期权理论在投资决策分析中的一致性 .     

Real R&;D options with time-to-learn and learning-by-doing

We model R&D efforts to enhance the value of a product or technology before final development. Such efforts may be directed towards improving quality, adding new features, or adopting technological innovations. They are implemented as optional, costly and interacting control actions expected to enhance value but with uncertain outcome. We examine the interesting issues of the optimal timing of R&D, the impact of lags in the realization of the R&D outcome, and the choice between accelerated versus staged (sequential) R&D. These issues are also especially interesting since the history of decisions affects future decisions and the distributions of asset prices and induces path-dependency. We show that the existence of optional R&D efforts enhances the investment option value significantly. The impact of a dividend-like payout rate or of project volatility on optimal R&D decisions may be different with R&D timing flexibility than without. The attractiveness of sequential strategies is enhanced in the presence of learning-by-doing and decreasing marginal reversibility of capital effects.