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。     

Using FSBT technique with Rough Set Theory for personal investment portfolio analysis

This study proposes a novel Forward Search and Backward Trace (FSBT) technique based on Rough Set Theory to improve data analysis and extend the scope of observations made from sample data to solve personal investment portfolio problems. Rough Set Theory mathematically classifies data into class sets. The class set with the most objects may generate one decision rule. The rules generated from RST are rough and fragmented, that are very difficult to interpret the information. An empirical case is used to generate more than 85 rules by the RST method in comparison with FSBT method which only generated 14 rules. This result can show our proposed method is better than traditional RST method based on class sets that contain the most objects. Much of human knowledge is described in natural language. It is a very important thing to convert information from computer databases into normal human language. Sample data taken from features with the same backgrounds are used to compile different portfolios that investment companies and investment advisors can employ to satisfy the investor’ needs. The method not only can provide decision-making rules, but also can offer alternative strategies for better data analysis. We believe that the FSBT technique can be fully applied in research on investment marketing.     

Optimal portfolio choice for an insurer with loss aversion

The problem of optimal investment for an insurance company attracts more attention in recent years. In general, the investment decision maker of the insurance company is assumed to be rational and risk averse. This is inconsistent with non fully rational decision-making way in the real world. In this paper we investigate an optimal portfolio selection problem for the insurer. The investment decision maker is assumed to be loss averse. The surplus process of the insurer is modeled by a Lévy process. The insurer aims to maximize the expected utility when terminal wealth exceeds his aspiration level. With the help of martingale method, we translate the dynamic maximization problem into an equivalent static optimization problem. By solving the static optimization problem, we derive explicit expressions of the optimal portfolio and the optimal wealth process.     

From social welfare ordering to acyclic aggregation of preferences

One way to overcome Arrow's impossibility theorem is to drop the requirement that the collective preference be transitive. If it is quasi-transitive (strict preferences are transitive) an oligarchy emerges. If it is only acyclic, many non-oligarchic aggregation rules are available, yet the resulting decision rules are poorly decisive: Nakamura's theorem characterizes acyclic and neutral Arrowian aggregators. We propose a parallel characterization of acyclic and anonymous aggregation methods.     

Applying the maximum NPV rule with discounted/growth factors to a flexible production scale model

This study examines the maximum net present value of the market entry and exit thresholds derived by the traditional net present value method and combines the real options approach for the project investment or disinvestment. The discounted and growth factors are incorporated into the proposed entry and exit models, facilitating the complicated calculations required to identify the discounted and growth rates so as to assess and determine the expected present value of uncertain cash flow streams. Consequently, this investigation successfully combines applying the maximum net present value method and the real options approach to decision-making with the simple consideration of the discounted and growth factors in the flexible production scale model.     

Alternative optimality criteria of portfolio selection based upon threshold stopping rule

This paper proposes two types of alternative criteria of optimality for the continuous time portfolio selection problem. The optimality criteria, the so–called Laplace–Stieltjes transform (LST) criteria, are based on the assumption that the financial agent has a target level for the wealth accumulation process. These criteria are closely related to the so–called threshold stopping investment rule. We analytically derive the LST criteria and numerically compare them with the well–known Kelly criterion. It is shown that the portfolio strategies suggested may overcome the problem that the growth portfolio is often overestimated in several investment situations.     

考虑破产控制的多期模糊资产-负债组合优化模型

在实际的投资决策过程中,一些投资者需要同时管理资产和负债,因此本文研究考虑破产控制和偿债行为的资产-负债管理问题。假设风险资产的收益率和负债的增长率为模糊数,用资产-负债组合的可能性期望和下半绝对偏差度量其收益和风险,以最大化最终期望净财富和最小化最终累积风险为目标,建立了允许限制性卖空的多期模糊资产-负债组合优化模型。然后,设计了一个基于粒子群算法和模拟退火算法的混合智能算法对模型进行求解。最后,通过实例分析说明了所设计算法与传统粒子群算法相比具有更好的优化性能和稳定性。本文所提出策略可以为需要同时管理资产和负债的投资者提供决策支持。     

允许投资组合条件下概率准则

概率准则具有一定的现实意义，其投资决策是以期望贴现资产为导向的．本文讨论了完备标准动态金融市场中在允许投资组合条件下的概率准则问题，得到了准则函数，贴现资产过程以及最优允许投资组合过程的解析表达式．期望贴现资产越大，准则函数越小。     

On the risk-equivalence of two methods of randomization in statistics

For statistical decision problems, there are two well-known methods of randomization: on the one hand, randomization by means of mixtures of nonrandomized decision functions (randomized decision rules) in the game “statistician against nature,” on the other hand, randomization by means of randomized decision functions. In this paper, we consider the problem of risk-equivalence of these two procedures, i.e., imposing fairly general conditions on a nonsequential decision problem, it is shown that to each randomized decision rule, there is a randomized decision function with uniformly the same risk, and vice versa. The crucial argument is based on rewriting risk-equivalence in terms of Choquet's integral representation theorem. It is shown, in addition, that for certain special cases that do not fulfill the assumptions of the Main Theorem, risk-equivalence holds at least partially.     

Chisini means and rational decision making: equivalence of investment criteria

A plethora of tools are used for investment decisions and performance measurement, including net present value, internal rate of return, profitability index, modified internal rate of return, average accounting rate of return. All these and other known metrics are generally considered non-equivalent and some of them are regarded as unreliable or even naïve. Building upon Magni (Eng Econ 55(2):150–180, 2010a, Eng Econ 58(2):73–111, 2013)’s average internal rate of return, we show that the notion of Chisini mean enables these tools to be used as rational decision criteria. Specifically, we focus on 11 metrics and show that, if properly used, they all provide equivalent accept–reject decisions and equivalent project rankings. Therefore, the intuitive notion of mean is the founding basis of investment decision criteria.     

Regret aversion and annuity risk in defined contribution pension plans

The high value of the implicit option to choose a retirement date at which interest rates are particularly high and life annuities relatively cheap, leads to the possibility to introduce regret aversion in the retirement investment decision of defined contribution plan participants. As a remedy for regret aversion in retirement investment decisions, this paper develops and prices a lookback option on a life annuity contract. We determine a closed-form option value under the restriction that the option holder invests risklessly during the time to maturity of the option and without the guarantee that the exact amount of retirement wealth is converted into a life annuity at retirement. Thereafter the investment restriction is relaxed and the guarantee of exact conversion is imposed and the option is priced via Monte Carlo simulations in an economic environment with a stochastic discount factor. Option price sensitivities are determined via the pricing of alternative options. We find that the price of a lookback option, with a maturity of three years, amounts to 8%–9% of the wealth at the option issuance date. The option price is highly sensitive to the exercise price of the option, i.e. pricing alternative options (e.g. Asian) substantially lowers the price. Time to maturity and interest rate volatility are other important option price drivers. Asset allocation decisions and initial interest rates hardly affect the option price.     

Performance evaluation of some special classes of weighted majority rules

The main concern of this paper is the performance evaluation of four classes of decision rules: the expert rule, the balanced expert rules, the simple majority rule, and the restricted simple majority rules. Employing the uncertain dichotomous choice model we first establish the necessary and sufficient conditions for the optimality of these four types of decision rules.For small groups consisting of less than six members the optimality conditions cover all the potentially optimal decision rules. Consequently, we are able to pursue a complete analysis of the small group cases. The analysis of the special (small group) cases as well as that of the general (n-member group) cases is based on the assumption that individual decisional skills are uniformly distributed. In evaluating the quality of a decision rule we resort to four alternative criteria: the expected optimality likelihood of the rule, the expected probability of yielding a correct collective decision given complete information on decisional skills, the expected probability of yielding a correct collective judgement given complete inability of skills verification, and, finally, the sensitivity of the rule to skills verifiability.     

基于双论域模糊粗糙集的应急决策模型与方法

以突发危机事件应急决策为应用背景,讨论了双论域上模糊粗糙集的基本理论,建立了基于模糊相容关系的双论域模糊粗糙集模型. 在此基础上,把突发危机事件应急决策转化为一个具有模糊决策对象的双论域决策近似空间上的粗糙近似问题,构建了基于双论域模糊粗糙集的应急决策模型.首先在双论域近似空间中计算模糊决策对象的上(下)近似,进而结合经典非确定型决策的思想给出了突发危机事件应急决策的规则.同时,给出了模型的算法.该模型给出了一种在不完全信息环境下应急决策的方法,给出了在充分考虑决策者个人偏好信息基础上的决策置信度以及最优决策规则.该方法能够比较充分地符合应急决策信息不充分、资源有限以及时间紧迫的基本特征, 进而对突发危机事件应急决策提供科学的理论基础和现实的决策方法.最后,通过应用算例说明了模型的应用过程,结果验证了本文给出模型的有效性。     

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 .     

Optimization of a highway project planning using a modified genetic algorithm

This paper proposes an optimization method for a national-level highway project planning based on a modified genetic algorithm. The proposed method adds to the existing methods by integrating various planning elements into a single system. A simulation model is used in order to determine the best investment strategy with regard to net present value, time deviation from the initial plan and discrepancy between available resources and investment costs by taking into account economical, social, traffic and political factors. The outcome is a project schedule with an optimized cash flow. The proposed method was tested using the example of the National Highway Programme in Slovenia.     

Comparison of selection rules for ordinal optimization

The evaluation of performance of a design for complex discrete event systems through simulation is usually very time consuming. Optimizing the system performance becomes even more computationally infeasible. Ordinal optimization (OO) is a technique introduced to attack this difficulty in system design by looking at “order” in performances among designs instead of “value” and providing a probability guarantee for a good enough solution instead of the best for sure. The selection rule, known as the rule to decide which subset of designs to select as the OO solution, is a key step in applying the OO method. Pairwise elimination and round robin comparison are two selection rule examples. Many other selection rules are also frequently used in the ordinal optimization literature. To compare selection rules, we first identify some general facts about selection rules. Then we use regression functions to quantify the efficiency of a group of selection rules, including some frequently used rules. A procedure to predict good selection rules is proposed and verified by simulation and by examples. Selection rules that work well most of the time are recommended.     

Evolutionary search for difficult problem instances to support the design of job shop dispatching rules

Dispatching rules are simple scheduling heuristics that are widely applied in industrial practice. Their popularity can be attributed to their ability to flexibly react to shop floor disruptions that are prevalent in many real-world manufacturing environments. However, it is a challenging and time-consuming task to design local, decentralised dispatching rules that result in a good global performance of a complex shop.An evolutionary algorithm is developed to generate job shop problem instances for which an examined dispatching rule fails to achieve a good solution due to a single suboptimal decision. These instances can be easily analysed to reveal limitations of that rule which helps with the design of better rules. The method is applied to a job shop problem from the literature, resulting in new best dispatching rules for the mean flow time measure.     

An examination of HMM‐based investment strategies for asset allocation

We develop and analyse investment strategies relying on hidden Markov model approaches. In particular, we use filtering techniques to aid an investor in his decision to allocate all of his investment fund to either growth or value stocks at a given time. As this allows the investor to switch between growth and value stocks, we call this first strategy a switching investment strategy. This switching strategy is compared with the strategies of purely investing in growth or value stocks by tracking the quarterly terminal wealth of a hypothetical portfolio for each strategy. Using the data sets on Russell 3000 growth index and Russell 3000 value index compiled by Russell Investment Services for the period 1995–2008, we find that the overall risk‐adjusted performance of the switching strategy is better than that of solely investing in either one of the indices. We also consider a second strategy referred to as a mixed investment strategy which enables the investor to allocate an optimal proportion of his investment between growth and value stocks given a level of risk aversion. Numerical demonstrations are provided using the same data sets on Russell 3000 growth and value indices. The switching investment strategy yields the best or second best Sharpe ratio as compared with those obtained from the pure index strategies and mixed strategy in 14 intervals. The performance of the mixed investment strategy under the HMM setting is also compared with that of the classical mean–variance approach. To make the comparison valid, we choose the same level of risk aversion for each set‐up. Our findings show that the mixed investment strategy within the HMM framework gives higher Sharpe ratios in 5 intervals of the time series than that given by the standard mean–variance approach. The calculated weights through time from the strategy incorporating the HMM set‐up are more stable. A simulation analysis further shows a higher performance stability of the HMM strategies compared with the pure strategies and the mean–variance strategy. Copyright © 2009 John Wiley & Sons, Ltd.     

Generalized evaluation in decision analysis

The paper presents a discussion on evaluation methods in decision analysis. The presentation begins with the discussion of the expected value rule for selection amongst a number of available courses of action. Then a number of other evaluation rules to either replace or supplement the expected value are presented. They are discussed from a choice rather than preference view. To improve the expected value rule (or any other similar rule), it is suggested that it should be supplemented with other, qualitative rules rather than engaging in further modifications in pursuit of the perfect rule. A characteristic of qualitative rules is that they do not rely on multiplying probabilities and values but treat them as separate numeric entities. Once a rule has been agreed upon, it can be applied to all the alternatives, provided there is a computational procedure for evaluating the alternatives under that rule. Delta dominance is introduced as a unifying concept for many of the dominance rules in current use. Dominance and threshold methods are discussed and the kinship between them is pointed out.     

Synthetic indicators of mutual funds’ environmental responsibility: An application of the Reference Point Method

Socially Responsible Investing (SRI) is broadly defined as an investment process that integrates not only financial but also social, environmental, and ethical (SEE) considerations into investment decision making. SRI has grown rapidly around the world in the last decades. In the last years, given the causes of the 2008 financial crisis, ethical, social, environmental and governance concerns have become even more relevant investment decision criteria. However, while a diverse set of models have been developed to support investment decision-making based on financial criteria, models including also social responsibility criteria are rather scarce.