基于风险投资家尽职调查的项目选择方法

风险投资作为一种新型的投融资体制,孕育着巨大的风险.因而,采取科学的投资决策方法与否直接关系到风险投资的成败.本文在风险投资家对处于尽职调查阶段的风险项目充分了解的假设下,提出了一种基于风险投资家尽职调查的项目选择方法,为风险投资家充分利用自己掌握的信息进行投资项目决策提供了思路和参考.     

我国企业投资决策方法选择的调查研究

通过对大样本调查问卷的统计分析,揭示了我国企业所选择的投资决策方法和企业特征之间的关系.研究结果表明,我国企业最常用的投资决策方法是回收期法;最常使用的折现率是同期银行的贷款利率;我国企业在投资决策时对财务风险的关注多于对利率风险和通货膨胀风险因素的关注.     

基于损失厌恶的基金管理者的投资决策模型

本文从风险约束的视角研究基金管理者呈损失厌恶的投资决策问题.用行为金融学的前景理论刻画损失厌恶,构建了以CVaR为风险约束的最大化管理者期望价值的投资决策理论模型.利用辅助函数得到了与原模型具有相同最优解的等价模型,并利用Monte Carlo模拟方法将等价模型转化为线性规划问题,通过求解等价模型得到了管理者的最优投资策略和努力水平.为了说明本文提出的模型和方法的有效性,用我国股市的数据进行了数值实例.本文的研究成果为基金管理者提供了投资决策的理论依据和方法.     

考虑背景风险的项目投资决策

在项目投资过程中不但面临项目风险,同时还面临背景风险,且背景风险与项目风险之间往往存在着一定的相关性。文章在已有研究的基础上,针对考虑背景风险的项目投资决策问题,分析了风险之间的相关性及相关程度对投资决策的影响。首先讨论了加性背景风险和乘性背景风险单独存在时,背景风险与项目风险之间的相关性对投资决策的影响;其次构建了两种背景风险同时存在情形下的投资模型,进而通过蒙特卡罗仿真方法给出不同相关程度下的仿真结果,在此基础上分析两种背景风险与项目风险之间的相关性及相关程度对投资决策的影响并给出相关研究结论。     

用Excel建立投资项目的风险分析模型

在实际投资活动中充满了不确定性。如果投资活动面临的不确定性比较小,一般可忽略它的影响,把投资决策视为确定情况下的决策。如果面临的不确定性(即风险)比较大,足以影响方案的抉择,那么就应对它们进行计量并在决策时加以考虑。投资风险分析的常用方法是风险调整贴现率法与肯定当量法。但这两种方法的计算非常繁琐,给决策者每次的投资风险分析带来极大的不便。这里,本人试着用Excel的有关工具建立一个投资项目的风险分析模型。一、风险调整贴现率法投资风险分析最常用的方法是风险调整贴现率法。这种方法的基本思想是对于高风险的项目,采…     

一种信息安全投资的智能化决策方法研究

当组织的信息系统因为漏洞而受到的威胁时,组织必须进行信息安全投资决策以减少损失.信息安全投资决策是一个多目标决策和NP难题.为精确解决组织的信息安全投资决策问题,本文提出一种改进的二进制的粒子群优化算法(PSO),帮助组织最优化的投资和实现最大化的弥补漏洞.为加快收敛速度,在传统的离散PSO中移植了一种记忆机制.经过实验,改进的算法具有更好的搜索效率和稳定性.为企业提供了一种简单有效的决策支持工具.     

代理冲突下企业多元化投资行为的实物期权分析

利用实物期权的方法,本文分别建立了以股东利益最大化以及企业价值最大化为目标时的负债企业多元化投资模型.通过两种决策目标下多元化投资政策的比较,分析了负债代理下股东存在的投资决策非最优化问题.结果发现,若负债企业在投资前后都不存在债务风险,股东的投资决策将符合企业价值最大化原则;若投资能使债务由无风险变为有风险,企业将过度投资;若投资前后都存在风险,企业将投资不足.     

基于条件风险值CVaR模型的房地产组合投资的风险度量与策略

降低房地产投资风险不仅是房地产企业、投资者关注的问题,更是降低金融风险的重要内容.本文着重研究了基于条件风险值(CVaR)模型的房地产组合投资风险度量问题,通过定义离散α-VaR、α-CVaR损失值以及α-FCVaR损失值的等价函数,建立了基于离散CVaR模型的房地产组合投资优化模型,通过计算得到在一定置信水平下的组合投资比例和风险损失,从而为房地产投资决策提供依据.论文用2003-2005年我国六大城市房价数据实验,结果表明控制房地产风险的一种主要策略是选择低风险的CVaR值的投资组合.     

基于风险价值偏好的最优投资决策分析

在传统金融理论中,用收益率与方差所构成的效用函数来指导投资者的最优投资决策,这一点在理论上存在一些的缺陷。本文根据行为金融理论中对风险偏好的描述,用风险价值来定量风险偏好,并用这种偏好来指导最优投资决策。     

负债代理冲突影响企业投资行为的实物期权分析

本文利用实物期权方法研究了负债代理冲突下的企业投资决策问题.与现有的研究文献不同,本文不仅考虑了无破产代理下的股东投资目标异化对企业投资决策的影响机理,而且分析了破产代理冲突所导致的企业投资决策扭曲问题.研究结果表明:负债企业股东通常存在过度投资现象,这种过度投资一方面来自投资目标异化影响下的股东对税收利益的过度追逐,另一方面来自策略性违约破产对股东投资风险的庇护作用.在较低负债水平下,前者是企业投资决策扭曲的主导机制;在较高负债水平下,后者的影响则更为显著.并且,高风险项目更容易产生投资目标异化下的投资扭曲,而破产代理下的高成长项目的投资扭曲则会更加严重.     

The relationship between burnout and risk-taking in workplace decision-making and decision-making style

This study aimed to investigate what decision-making styles might be exhibited by employees who experience burnout. Using a Work Risk Inventory (WRI), developed for this study, which included generic workplace scenarios, it was also explored whether such employees take relatively more risky decisions. Risk was conceptualised as the adoption of decisions that threaten one’s reputation at work, job performance and job security. The mediating effect of the likelihood and seriousness of the consequences of the worst that could happen in each given scenario on the relationships between dimensions of burnout and risk-taking was also tested. A total of 262 employees in various occupations completed an online survey, including measures on burnout, decision-making styles and the WRI. As predicted, dimensions of burnout – exhaustion, cynicism and professional inefficacy – correlated significantly with avoidant decision-making and negatively with rational decision-making. The seriousness of the consequences of the worst-case scenario occurring mediated the relationship between professional inefficacy and risk-taking. In the context of identifying mechanisms by which burnout leads to risky decision-making, the findings suggest that employees’ sense of professional inefficacy determines their risky decision-making. The contribution to theory and implications for practice are discussed.     

Best-worst multi-criteria decision-making method

In this paper, a new method, called best-worst method (BWM) is proposed to solve multi-criteria decision-making (MCDM) problems. In an MCDM problem, a number of alternatives are evaluated with respect to a number of criteria in order to select the best alternative(s). According to BWM, the best (e.g. most desirable, most important) and the worst (e.g. least desirable, least important) criteria are identified first by the decision-maker. Pairwise comparisons are then conducted between each of these two criteria (best and worst) and the other criteria. A maximin problem is then formulated and solved to determine the weights of different criteria. The weights of the alternatives with respect to different criteria are obtained using the same process. The final scores of the alternatives are derived by aggregating the weights from different sets of criteria and alternatives, based on which the best alternative is selected. A consistency ratio is proposed for the BWM to check the reliability of the comparisons. To illustrate the proposed method and evaluate its performance, we used some numerical examples and a real-word decision-making problem (mobile phone selection). For the purpose of comparison, we chose AHP (analytic hierarchy process), which is also a pairwise comparison-based method. Statistical results show that BWM performs significantly better than AHP with respect to the consistency ratio, and the other evaluation criteria: minimum violation, total deviation, and conformity. The salient features of the proposed method, compared to the existing MCDM methods, are: (1) it requires less comparison data; (2) it leads to more consistent comparisons, which means that it produces more reliable results.     

基于Mean-CVaR约束的股指期货动态套期保值模型研究

本文建立了基于最小化均值-条件风险价值( Mean-CVaR)的股指期货动态套期保值模型.模型的主要特点与贡献在于两方面:一方面,考察了置信水平和可变交易费用对最优套期保值决策的影响;另一方面,利用二元误差修正的时变条件相关GARCH模型估计套期保值比率,优点是不仅考虑了股指期货与现货价格序列之间存在的协整关系,而且更好地拟合了收益残差序列存在的异方差性与相关系数时变性的特征.最后通过对我国沪深300指数期货仿真交易的套期保值模拟与实证测算,得出能够动态调整的股指期货套期保值策略以实时追踪与控制风险.     

风险资产组合的均值—M有效前沿及其实证分析

本文基于由Carlo Acerbi(2002)提出的一类一致性风险度量—谱风险测度M,给出了谱风险测度的一些性质及构造谱密度的一种具体形式;重点讨论了正态情形下风险资产组合的均值—M有效前沿,探讨了其经济含义,并与经典的均值—方差有效前沿进行了对比研究,获得了若干深入的结果。由于期望短缺ES是特殊的谱风险测度,因此其对应的有效前沿是本文结果的特例。最后,本文利用前面的结论对深市和沪市的风险资产组合的均值—M有效前沿作了实证分析。     

Ensemble ranking: Aggregation of rankings produced by different multi-criteria decision-making methods

One of the essential problems in multi-criteria decision-making (MCDM) is ranking a set of alternatives based on a set of criteria. In this regard, there exist several MCDM methods which rank the alternatives in different ways. As such, it would be worthwhile to try and arrive at a consensus on this important subject. In this paper, a new approach is proposed based on the half-quadratic (HQ) theory. The proposed approach determines an optimal weight for each of the MCDM ranking methods, which are used to compute the aggregated final ranking. The weight of each ranking method is obtained via a minimizer function that is inspired by the HQ theory, which automatically fulfills the basic constraints of weights in MCDM. The proposed framework also provides a consensus index and a trust level for the aggregated ranking. To illustrate the proposed approach, the evaluation and comparison of ontology alignment systems are modeled as an MCDM problem and the proposed framework is applied to the ontology alignment evaluation initiative (OAEI) 2018, for which the ranking of participating systems is of the utmost importance.     

The robustness of linear models for decision-making

This paper elaborates on some issues discussed by Moskowitz, who presented evidence that linear multiple regression models, estimated from decisions made by individuals, often outperform the individuals themselves. In discussing his results, Moskowitz (1) suggested that inconsistency in information utilization by individuals may account for the relative superiority of regression models, and (2) expressed concern over the robustness of linear regression models to changes in (a) information environments, (b) weighting parameters, and (c) functional form of the model. This paper discusses reasons (in addition to inconsistency) for the relative superiority of model over man, and it summarizes recent research in psychology concerning the robustness of linear regression models (and linear models in general). This paper is supportive, rather than critical, of Moskowitz's research.     

基于幂风险谱和蒙特卡洛模拟的贷款优化配置模型

极端风险对于银行资产配置至关重要，尤其是次贷危机之后尾部风险以惨重的代价引起了金融机构的重视，传统条件风险价值CVaR、风险价值VaR不能有效度量尾部极端风险，因此本文基于幂风险谱和蒙特卡洛模拟构建了贷款组合优化配置模型，同时控制尾部极端风险和信用风险。本文一是通过损失-X_i越大、其风险权重φ_i也就越大的思路，构建幂风险谱PSR （Power Spectral Risk）最小的目标函数对极端风险进行控制，即弥补了CVaR同等看待尾部风险、忽略风险较大的损失应予以更大权重的不足，也同时弥补了VaR仅提供某一置信水平下资产损失的最大值、无法反映一旦超过这一数值的可能损失的弊端。二是通过蒙特卡洛模拟信用等级迁移引起贷款收益的变化情景，并以信用等级迁移后贷款组合损失越大、则风险厌恶权重越大的思路构建幂风险谱PSR最小为目标函数，以贷款组合的收益大于目标收益为约束，构建贷款优化配置模型，改变了现有研究贷款配置时没有同时控制信用风险和尾部风险的不足。对比分析结果表明：本文模型能够实现更高的收益风险比，即在单位幂风险谱PSR下能够实现较高的收益。     

应用复合极值理论估计动态流动性调整VaR

本文首次将一分钟内的交易差价(分内价差)的分布和日收益率的分布结合了起来进行分析,应用复合极值理论给出了动态流动性调整的VaR一种估计,同时得到动态流动性调整VaR的预测方法,最后对上海汽车股票(600104)和中国石化(600028)两只股票进行了实证分析。