基于实物期权理论的并购企业定价研究

实物期权方法的重要特征是能够定量地评价不确定性因素给项目带来的价值影响。本文应用期权理论分析M&A项目投资,实质上是引入了并购决策的动态计价算法,可以准确地估算由并购决策带来的未来选择权的价值,从而避免由于忽略未来选择权而导致的投资不足。在实际中,选择权价值的计算主要是借用金融期权定价的Black-Scholes模型和CRR模型来进行。     

电子商务投资——实物期权模型分析

电子商务投资具有投资不可逆性和较高的不确定性等特点,电子商务投资的不确定性因素形成了投资的机会价值。传统的电子商务投资决策方法存在对折现率的选取困难、现金流量预测不准以及不能反映管理的灵活性等缺陷,因而它忽视了电子商务投资的期权价值,常常低估电子商务投资项目的真实价值,从而导致错误的决策。将实物期权理论在电子商务投资决策中的模型分析作为研究的课题,运用实物期权理论与方法,研究电子商务投资在不确定性因素下的投资决策方法与评价模型,为电子商务投资决策提供了新的思路和决策方法。     

基于实物期权思想的转包生产决策

分析了传统转包决策方法的局限性,借鉴实物期权理论,提出了延迟期权、扩展期权、放弃期权、收缩期权和转换期权在生产中的实际意义.应用Black-Scholes期权定价模型和二叉树期权定价模型研究了基于实物期权的生产/转包决策方法,通过2种模型结果的比较,为面向未来价值的自行生产或转包生产的决策提供了理论依据.     

不确定收益下关键链项目缓冲前置分配模型

在关键链项目管理技术中,缓冲的设置和监控是决定项目计划稳定性和有效性的关键一环.但现有的理论对项目缓冲的分配却没有一个清晰的界定.由于工序在执行时具备可延迟的特性,我们把实物期权的思想引入项目缓冲的分配过程中,通过将缓冲区前置,设计不确定性的概率分布来建立一个基于实物期权的0-1整数规划模型.将关键链管理思想和最迟开工规则有机结合,使得时间缓冲能够在各个关键工序中的灵活分配,实现关键链项目管理期权价值最大化.     

期权方法在R＆D项目决策中的应用

本文简要分析了传统投资项目决策NPV法的缺陷与不足，提出从实物期权的角度来分析R＆D项目投资决策上的管理柔性，进一步揭示隐含在R＆D不确定性投资中的价值，最后对实物期权的应用提出一些改进建议。     

实物期权在基础设施BOT项目投资决策中的应用

从基础设施BOT项目的不确定因素出发,针对传统投资评价方法对基础设施BOT项目投资决策的局限性,在分析基础设施BOT项目具有实物期权特性的基础上,建立了基于推迟期权的投资决策模型,求解了投资机会价值和最优投资决策的临界值,最后通过举例验证了该投资决策模型应用于基础设施BOT项目的可行性.     

技术进步对专利价值影响的实物期权分析

传统的专利价值评价方法没有考虑专利投资的实物期权价值,存在很大的缺陷,即低估专利的价值.目前用实物期权来评估专利价值的文献又没有考虑技术进步对专利价值的影响,从而高估专利的价值.为了准确评估专利的价值,本文将考虑技术进步对专利价值的影响,用跳-扩散过程来描述技术进步过程.通过介绍专利评估的实物期权方法,再对不考虑技术进步时专利评估的实物期权方法和存在技术进步时专利评估的实物期权方法进行详细的介绍,并对有竞争条件和无竞争条件下专利的实物期权价值进行比较,从而提高引入技术进步来评估专利价值的准确性.     

企业信息化投资的实物期权决策方法及应用

针对传统方法在企业信息化投资评价中的不足,根据企业信息化项目投资与美式分红期权投资的特征相似性,将期权理论引入到企业的信息化投资中,研究了不同投资评价周期下企业执行投资的最优时点,建立了实物期权决策模型.实例应用表明,企业的评价周期越短,企业执行投资的最优时点就越提前.     

基于复合实物期权的高新技术项目风险管理

针对由于风险因素众多、不确定性大而导致的高新技术项目成功率低的问题,在分析项目面临的风险、风险与复合期权种类的对应关系后,结合项目自身的特点,对项目所含复合实物期权进行设计构造.通过考虑项目内各种期权之间的双向作用,以及高新技术项目的特殊性,提出了修正的复合实物期权二项式评价方法.实例分析表明,应用本文方法能够实现项目风险管理与项目价值目标的有机统一.     

基于敲出障碍期权和博弈理论的项目投资决策分析

阐述了实物期权的基本原理和敲出障碍期权的内涵及其定价求解，提出了基于敲出障碍期权的实物期权定价方法和博弈理论的项目投资决策分析，分析了双寡头市场结构下的项目投资决策，给出了算例分析。     

A real options approach to project management

When scheduling an uncertain project, project management can wait for additional (future) information to serve as the basis for rescheduling the project. This flexibility enhances the project's value by improving its upside potential while limiting downside losses relative to the initial expectations. Using traditional techniques such as net present value (NPV) or decision tree analysis (DTA) can often lead to misleading results. Instead, a real options analysis should be preferred. The potentials of a real options approach to project management are discussed with an example and future research directions are highlighted.     

A real option based model for the valuation of patent protected technological innovation projects

Decision Tree Analysis and Internal Rate of Return, do not properly consider uncertainty and flexibility, which are crucial for both valuating a project and the related decision-making process. Usually, uncertainty and managerial flexibility have been regarded as a factor that needs to be reduced; nevertheless, Real Option analysis recognizes that both may generate value, since both allow managers to decide on the investment on a project as time unfolds. This research proposes the development of a model and a tool based on real options that supports decision-makers in the valuation process of uncertain projects. The model originally developed by Schwartz and later adapted and modified by Ernst et al. is used as a baseline for the tool. The objective is to develop an easier-to-use-tool for decision-makers to valuate patent protected technological innovation projects which uses fewer variables than the actual model. The expected users are Technology Transfer Offices, which can support the decision-making process of investing on risky projects for its further commercialization. The main results of the model are the probability distribution of the project value and the percentage of times that profit is generated, which are critical factors when deciding to invest in a technological project.     

基于风险承受力的石油企业最优投资决策

通过引进风险承受力理念,改进Markowitz投资组合模型进行项目选择,辅以MAUT多属性分析技术作为财务、技术、环境、地质等因素的综合决策依据,并运用某石油企业的实际数据进行实证分析检验。研究将决策者对管理属性的风险承受力、相对重要性等因素加以综合考虑,通过建立决策分析与投资组合管理之间的联系,提升整体的决策过程,最终促进企业业绩的价值提升。     

存在融资的模糊决策投资组合模型的研究及应用

利用应用效果较好的均值-半偏差投资组合模型对存在融资情况的投资组合进行分析研究。将存在融资情况的均值-半偏差模型的收益和风险目标进行模糊化,并构造了使用较多且效果佳的线性隶属度函数μmax(x)和μmin(x)。运用模糊决策理论引进变量μ将模糊环境下存在融资的双目标模型转化为线性的基于模糊决策存在融资的投资组合模型。本模型不仅简化了模型的计算量,同时也将投资者的主观投资意愿表示清楚。最后通过实例说明了模型的实用性和有效性。     

Project Portfolio Ranking based on the Strategic Contribution Efficiency

Project portfolio management is proved to be remarkable for an enterprise to attain competences. When selecting project portfolios,enterprises are willing to know which one has the largest return on investment rate when realizing enterprise strategy. A methodology for project portfolio ranking by adopting the concept of Strategic Contribution Efficiency（ SCE） is proposed. SCE acts as the measure that demonstrates what degree a project portfolio would contribute to enterprise strategy at specific cost. Evaluation criteria are established according to the practical requirements of enterprises. Data Envelope Analysis（ DEA） is combined with fuzzy set to calculate SCE and the ranking,which takes project portfolio as a whole rather than evaluates individual projects separately and considers information imprecision at the same time. At last,a numerical example is illustrated the specific process of project portfolio ranking based on SCE,from the portfolio generation to analysis,and the efficiency of proposed model is verified.     

带有交易成本的均值——方差——下半方差投资组合模型

投资组合选择研究为投资决策和风险管理提供了可量化的途径和科学决策的依据．本文引入了非凹非凸的典型交易成本函数,建立了含有交易成本函数的均值--方差--下半方差投资组合模型．考虑到不同的投资者对风险的厌恶程度不同,引入风险厌恶系数,把双目标的投资组合优化模型转化为单目标的投资组合优化模型,并运用教与学算法对模型进行了求解,得到不同收益下的最优投资组合,同时给出了投资组合的有效边界,最后对算法的优越性进行了分析,得到了比较好的仿真结果．     

非对称信息条件下外部性期权问题分析

描述了外部性期权投资者和经营者价值函数,分析了不同信息条件下外部性期权的最优投资决策.在非对称信息条件下,外部性期权经营者对于项目价值信息隐匿,是一个具有逆向选择的委托代理问题.设计了以外部性期权管理当局利润数学期望最大为目标函数,以控污成本和污染预防水平作为状态方程的最优控制问题.应用极大值原理,得出了外部性期权最优控污成本和污染评价水平的求解方案.最后,进行了外部性期权的仿真实验,验证了外部性期权上的分析结果.     

Dynamic portfolio optimization under multi-factor model in stochastic markets

We consider the modeling and solution of the multi-period portfolio selection problem in stochastic markets with bankruptcy risk control. This research differs from current results in the following ways: rather than in terms of return moments, the stochastic evolution of the market is directly described in terms of investment returns by a finite-state Markov chain; the multi-factor model is initially introduced in the modeling process to better control bankruptcy risk and to cope with large-scale portfolio selection problems; the stable distributions are adopted to describe factors’ fluctuations to properly reflect the return distribution characteristics of risky assets; the bankruptcy risk in each period is flexibly controlled by utilizing the properties of the multi-factor model and restricting the portfolio loss caused by each factor; a specific bi-level programming method is proposed to find the analytical investment strategy; the practical significance and good performance of the stage-wise investment decision, when not optimal, are verified. Empirical results are finally provided to illustrate the suitability and practical performance of the new model and the derived explicit investment strategy.