投资项目的期权评价与最优投资规则

本文介绍了不确定环境下的投资项目的期权评价方法和最优投资规则，研究了单期项目和连续投资项目的投资决策问题，探讨了实物期权评价方法与传统的净现值评价方法中最优投资规则的差异，并对影响最优投资规则的差异因素进行了敏感性分析，得出了直观而有实用价值的结论。     

实物期权方法在自主创新项目投资决策中的应用

传统的投资决策方法由于蕴含着不确定性和可逆转性的假设使其不适应于高风险、高收益并存的自主创新项目投资决策.将实物期权思想融入自主创新项目投资决策方法,考虑了项目由于柔性经营的期权价值,能更准确地反映项目的价值,从而提高投资决策的科学性和合理性.从实物期权理论的基本原理出发,通过具体实例对比说明实物期权方法应用于自主创新项目投资决策的优势.     

合作竞争条件下R&D项目投资决策分析

R&D项目的成功会为高新技术企业带来巨大收益,但是其研发过程中存在着技术风险、商业风险和突发风险等所带来的多种不确定性。为了应对这些不确定性,一些高新技术企业往往结成追求联盟整体利益最大化的成本共享联盟来进行R&D项目投资,然而由于不进行技术共享并争夺研发成功后的收益,联盟中的企业又会在合作的同时进行竞争,这就需要企业对R&D项目的估值非常的精确,以便在合作竞争条件下做出收益最大的最优投资决策。市场中两个合作竞争的高新技术企业各自拥有四种投资决策:成为市场先行者或跟随者,立刻与另一企业共同投资,与另一企业共同选择先等待时机再进行投资。本文以这两个高新技术企业为例,利用欧式期权理论量化了多种不确定性,建立相应的R&D项目投资决策数学模型,对R&D项目的投资时机和决策收益进行评估。当成本共享联盟整体收益最大时,得到的两个高新技术企业做出的投资决策即为在合作竞争条件下R&D项目投资中各自的最优投资决策,最后通过Shapley值的计算可对联盟中企业各自的收益进行合理分配。     

基于实物期权定价方法的林业碳汇项目投资决策仿真研究

文章针对林业碳汇项目投资决策的复杂性、动态性和不确定性过程,利用林业—碳汇共同经营决策模型计算林业碳汇项目在投资期内的期望价值,采用实物期权定价方法对不同阶段不同策略下的林业碳汇项目价值进行评估,同时提出了多主体仿真建模方法,利用NetLogo仿真软件对林业碳汇项目投资决策过程进行动态模拟。仿真系统中涉及到的主体有林地、CO₂和投资者,投资者主要是作为观察者的身份,在不同阶段会做出不同的投资策略。模拟仿真三种不同状态下投资者的决策变化:一是传统林业投资动态模拟,不包含碳汇和期权因素动态模拟;二是引入碳汇市场后的林业投资动态模拟;三是引入碳汇市场和期权后林业投资动态模拟。NetLogo仿真分析结果表明引入碳汇市场可以提高投资者的收益并改变投资者的经营策略,同时引入期权,不仅增加了投资者的积极性而进行扩张投资,还可以更好地发挥林木碳汇功能,体现林业的生态价值及经济价值。     

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。     

决策依赖不确定条件下基于复合实物期权估值的工程系统投资决策研究

不确定性是复杂工程系统的内在属性,在决策依赖不确定条件下对工程系统的投资决策需考虑不确定性与决策过程之间的交互作用,使得投资决策问题的求解非常困难.提出了决策依赖不确定条件下复合实物期权估值的最小二乘模拟算法,方法较好地解决了在决策依赖不确定条件下由于不同期权价值相互耦合所带来的计算复杂性,进一步拓展了最小二乘模拟算法在期权估值中的应用,基于该方法,可以比较方便地解决决策依赖不确定条件下工程系统投资决策问题.     

技术创新项目投资决策方法研究

利用科学实用的多目标决策方法对企业不同技术创新投资项目进行决策评估,可为企业提供重要的决策支持,具有重要的现实意义.结合多目标决策理论和模糊数学的方法,在分析技术创新项目特点的基础上,提出了一种基于模糊数学的多目标决策方法.应用算例表明该方法用于技术创新项目投资决策是合理可行的.     

不确定性投资决策中的期权博弈分析

本文应用期权博弈理论方法分析了存在竞争条件下的不确定性投资决策问题.建立了一个对称双寡头模型,用实物期权方法计算了模型中的领先者、跟随者和同时投资者的价值函数和投资临界点.     

最优投资决策的一个统计渐近算法

设■=(X_1,…,X_m)为市场收益随机向量,具有联合概率分布F(■)=F(x_1,…,x_m),又设■=(b_1,…,b_m)为一个资本投资决策,其中b_i≥0,∑_ib_i=1。称■(■,■)=∫log(∑_ib_i·x_i)dF(x_i,…,x_n)为(■,■)的倍率.一个决策■~*被称为是最优的,如■(■,■~*)=max W(■,■)。资本投资的一个核心问题就是寻找最优的■~*。许多论文都是在F(■)已知条件下讨论这个问题。本文首次给出关于■~*在m=2时的统计算法,并证明了这个估计量是一个一致统计量。     

A policy improvement method for constrained average Markov decision processes

This brief paper presents a policy improvement method for constrained Markov decision processes (MDPs) with average cost criterion under an ergodicity assumption, extending Howard's policy improvement for MDPs. The improvement method induces a policy iteration-type algorithm that converges to a local optimal policy.     

The impact of investment lags on investment decision

This paper suggests a valuation framework for an investment project through the concept of real options. Generally, in real asset world, decision time and its payment time are not identical. This so-called investment lag problem should be considered when valuing real assets. When investment lags exist, firms’ accommodation capacities play important roles. In this paper, the real effect of investment lag on investment value is tested upon various conditions. We show the valuation process of real assets under the risk-neutral world. The closed-form formula is also provided for valuing real assets, including R&D project.     

Developing a straightforward approach for group decision making based on determining weights of decision makers

Group decision making is an active area of research within multiple attribute decision making. This paper assumes that all the decision makers (DMs) are not equally qualified to contribute equitably to the decision process. The aim of this paper is to develop an approach to determine weights of DMs, in which the decision information on alternatives with respect to attributes, provided by each DM, is represented in the form of interval data. We define the average of all individual decisions as the positive ideal decision (PID), and the maximum separation from PID as the negative ideal decision, which are characterized by a matrix, respectively. The weight of each DM is determined according to the Euclidean distances between the individual decision and ideal decisions. By using the obtained weights of DMs, all individual decisions are aggregated into a collective decision. Then the alternatives is ranked based on the collective decision. Meanwhile, this paper also gives a humanized decision method by using an optimistic coefficient, which is used in adjusting the relative importance between profit and risk. Finally, we give an example to illustrate the developed approach.     

An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring

Credit risk analysis is an active research area in financial risk management and credit scoring is one of the key analytical techniques in credit risk evaluation. In this study, a novel intelligent-agent-based fuzzy group decision making (GDM) model is proposed as an effective multicriteria decision analysis (MCDA) tool for credit risk evaluation. In this proposed model, some artificial intelligent techniques, which are used as intelligent agents, are first used to analyze and evaluate the risk levels of credit applicants over a set of pre-defined criteria. Then these evaluation results, generated by different intelligent agents, are fuzzified into some fuzzy opinions on credit risk level of applicants. Finally, these fuzzification opinions are aggregated into a group consensus and meantime the fuzzy aggregated consensus is defuzzified into a crisp aggregated value to support final decision for decision-makers of credit-granting institutions. For illustration and verification purposes, a simple numerical example and three real-world credit application approval datasets are presented.     

Decision Analysis and Real Options: A Discrete Time Approach to Real Option Valuation

In this paper we seek to enhance the real options methodology developed by Copeland and Antikarov (2001) with traditional decision analysis tools to propose a discrete time method that allows the problem to be specified and solved with off the shelf decision analysis software. This method uses dynamic programming with an innovative algorithm to model the project’s stochastic process and real options with decision trees. The method is computationally intense, but simpler and more intuitive than traditional methods, thus allowing for greater flexibility in the modeling of the problem.     

Monotone optimal decision rules and their computation

For a given objective functionw(x, a) onX × A, a maximizinga=(x) has to be determined for eachx in the totally ordered setX. We give conditions onw such that there is a monotone which can be computed recursively ifA is finite.     

The design of a database for multiperson decision support

The MEDIATOR approach to implementing negotiation support systems views collaborative decisions as complex, evolving data objects to be managed by an extended database management system. The paper outlines the requirements and a rough design for such a DBMS. Specifically, our approach represents decision problems as multispatial mappings that eventually lead from real-world observations to group utilities. Group decision processes are represented as nested transactions which collaboratively design this mapping data structure, controlled by group communication norms represented as integrity constraints. The paper concludes with some implementation considerations, using a conceptual model base management approach.     

The majority decision function for trees with 3 leaves

Kenneth May in 1952 proved a classical theorem characterizing simple majority rule for two alternatives. The present paper generalizes May’s theorem to the case of three alternatives, but where the voters’ preference relations are required to be trees with alternatives at the leaves. This paper with title “May’s Theorem for Trees” was presented at the joint DIMACS-LAMSADE workshop on Computer Science and Decision Theory, Université Paris-Dauphine, Paris 27–29 October 2004. It appeared in the proceedings Annales du LAMSADE 3 (2004), 259–266.