基于动态损失厌恶投资组合模型的最优资产配置与实证研究

从行为金融学的角度考虑投资者损失厌恶的心理特征,建立预期效用最大化的动态损失厌恶投资组合优化模型。以我国股票市场为依托,将市场分为上升、下降和盘整三种状态,研究动态损失厌恶投资组合模型的最优资产配置和绩效表现,并与静态损失厌恶投资组合模型、M-V投资组合模型和CVaR投资组合模型进行比较。最后,在具有交易成本的条件下对动态模型进行稳健性检验。得出结论：不同情况下,动态损失厌恶投资者具有不同的最优资产配置比例,且动态损失厌恶投资组合模型明显优于静态模型、M-V投资组合模型和CVaR投资组合模型。     

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CVaR两步核估计量的投资组合管理

在不做任何分布假设的条件下,利用非参数核估计方法对风险度量条件风险价值(conditional value-at-risk,CVaR)进行估计,得到CVaR的两步核估计公式.然后用估计出来的CVaR代替理论上的CVaR建立均值-CVaR模型,实现对风险估计与投资组合优化同时进行,并基于迭代思想设计求解该模型的简单算法.蒙特卡洛模拟结果表明基于两步核估计方法的投资组合优化模型和算法比现有的方法更加有效,估计出来的组合边界误差更小.引入无风险资产后,文中的模型和算法同样适用.最后,为说明其应用价值,采用中国A股市场的日收益率数据进行了实例分析.     

基于小波分析的多期夏普比率及实证研究

用风险价值代替标准差作为夏普比率中投资组合风险的度量,并应用修正的VaR计算方法解决收益率序列非正态分布时的风险度量问题.进一步地将小波分析引入夏普比率,利用小波函数的尺度变化与不同的投资期限相时应,建立了基于小波分析的多期夏普比率评价模型,并以我国经济背景为依托,选择上证八只封闭式基金进行研究.结果表明,把小波分析引入夏普比率可以解决投资组合业绩的多期评价问题.     

VaR之下厚尾分布的最优资产组合的收敛性

主要研究在VaR风险度量之下,收益具有厚尾性质的资产的投资组合问题.证明了基于尾部分布二阶展开的最优投资组合收敛于基于尾部分布一阶展开的最优投资组合.因此,对于VaR风险度量之下的最优投资组合问题,如果要求的风险承受水平充分低,则只需要利用尾部分布的一阶展开代替厚尾部分布进行近似计算,就可以达到满意的精度,从而不需要进行复杂的高阶运算.     

V aR 之下厚尾分布的最优资产组合的收敛性

主要研究在V aR 风险度量之下, 收益具有厚尾性质的资产的投资组合问题. 证明了基于 尾部分布二阶展开的最优投资组合收敛于基于尾部分布一阶展开的最优投资组合. 因此, 对于 V aR 风险度量之下的最优投资组合问题, 如果要求的风险承受水平充分低, 则只需要利用尾 部分布的一阶展开代替厚尾部分布进行近似计算, 就可以达到满意的精度, 从而不需要进行复 杂的高阶运算.     

基于Copula-SV-GPD模型的投资组合风险度量

对于多元金融资产组合,针对资产收益的厚尾性、波动的异方差性及资产间的非线性相关结构等特征,采用SV-t模型与极值理论结合刻画单个资产收益的波动性及尾部分布特征,应用Copula函数处理多元资产间的相关性,并结合Monte Carlo模拟对投资组合进行风险测度.通过对华安创新基金的实证分析结果表明,基于SV-GPD的边缘分布模型能有效地刻画金融资产收益时序并较为精确地处理资产收益尾部的异常变化,相比其他风险度量模型具有更好的优越性,基于Copula-SV-GPD模型的多元资产组合对风险测度能力更强,能有效地管理投资风险.     

国际油价与中美股价的相依关系研究——基于不同行业数据的分析

石油市场和股票市场作为现代经济中两个重要的市场,在经济活动中发挥着重要的作用。二者之间的关系对研究市场间的价格波动和风险传递有着重要的意义,本文通过vine copula模型对国际油价和中美两国股价之间相依关系进行分析,并将得到的相依关系运用到风险管理中。利用国际油价和中美各十个行业股票价格指数进行相依关系建模,得到相应的相依结构和相依关系,选择出与油价相依关系较强的行业股票价格指数和油价构建投资组合,利用相依关系模拟出收益率数据,度量投资组合的风险。实证研究结果表明中美两国的行业股票价格指数与国际油价的相依关系存在着显著的不同,中国行业股票价格指数与国际油价之间的相依关系要弱于美国行业股票价格指数与国际油价的相依关系;同时利用相依关系组成投资组合,对两组投资组合进行风险度量,风险度量的结果显示vine copula-GARCH能对具有较强的相依关系的变量组成的投资组合风险有很好的估计。     

不完备市场中再保险-投资的M-V及M-VaR最优策略

本文研究不完备市场中的保险公司再保险-投资问题.在保险公司盈余过程服从扩散过程的假设及不完备市场条件下,通过求解带约束的二次优化问题和二次优化对偶问题,分别得到均值-方差(M-V)模型和均值-在险价值(M-VaR)模型下保险公司再保险-投资问题的最优常数再调整策略及其有效前沿,对两种模型下的结论进行比较发现:两种模型下的最优常数再投资策略都表现为特定"共同基金"的倍数,但对最优倍数的选择不一定相同;两种模型下的再保险-投资有效前沿都表现为射线,但射线的起始点及斜率(风险价格)不一定相同.     

CRMW风险缓释效用目标跟踪的债券投资组合优化策略研究

为缓释债券市场违约风险,央行着力推进信用风险缓释工具CRMW(信用风险缓释凭证)的发展,关于CRMW风险缓释能力度量及CRMW在债券投资组合中的应用成为了亟待解决的关键问题。为此,本文借鉴CVaR思想提出了“CRMW风险缓释效用”以度量CRMW对债券违约风险缓释能力,借助概率分位点理论定义债券的动态风险并制定了动态风险缓释跟踪目标,基于此跟踪目标探讨带有CRMW的债券投资组合优化策略问题。研究结果表明,在保证目标投资收益率的前提下,债券最优投资组合可达到风险缓释效用的目标,使其同时实现转移风险和保障收益的双重目的,且该投资组合优化策略表现出良好的抗风险性能。     

基于技术融合的企业研发勾结研究

随着技术融合的日益盛行,产业融合的趋势越来越显著,企业跨产业的合作屡见不鲜。这种技术融合推动下的新竞合动态,迫使企业重新思考创新战略:即,企业如何突破原有产业边界,通过跨技术领域的合作创新,来降低成本、增加产量、提高企业利润、增进社会福利。因此,本文针对目前企业采用最频繁的合作创新模式--研发勾结(R&D Cartelization),在D'Aspremont二阶段模型的基础上,通过构建相应的博弈模型,研究了不同的产品替代系数、技术溢出系数以及创新系数对合作企业均衡成本、均衡研发投资、均衡产量和均衡利润的影响,并进行了相关案例分析。     

不允许卖空下证券投资组合的区间二次规划问题

本文基于经典的Markowitz均值-方差模型,针对市场上不允许卖空的情况,提出了证券投资组合的区间二次规划模型,通过应用区间数排序方法(区间序关系、区间可能度和区间可接受度),给出了两种证券投资组合的区间非线性优化的数学转化模型,从而将不确定性证券投资组合模型转化为确定性的证券投资组合二次规划模型进行求解,并对由本文给出的三种求解方法与传统方法进行了比较。     

Slack free MEA and RDM with comprehensive efficiency measures

This paper extends two directional distance function models, the Multi-directional Efficiency Analysis (MEA) Model and the Range Directional Model (RDM), in order to account for any type of technical inefficiency, i.e. both directional and non-directional inefficiencies. We first focus on the variable returns to scale (VRS) case, because both VRS-MEA and RDM are translation invariant models, which mean that both models are able to deal with negative data. Our main result is the definition of a new comprehensive efficiency measure which is units invariant and translation invariant and covers both models. Secondly, we introduce the RDM model under constant returns to scale (CRS) together with a new comprehensive efficiency measure.     

因特网上有害信息传播模型研究

因特网上有害信息带来的安全问题已经受到越来越多的关注.有害信息自由传播模型描述了有害信息在治理措施不完善情况下的传播规律,受限传播模型描述了有害信息在存在一定治理措施情况下的传播规律.在仿真试验的基础上,对上述模型中各参数的影响也进行了讨论,并在受限传播模型基础上提出了治理粒度的概念,为评价有害信息的治理效果提供了一种途径.     

Methods to Explore Uncertainty and Bias Introduced by Job Exposure Matrices

Job exposure matrices (JEMs) are used to measure exposures based on information about particular jobs and tasks. JEMs are especially useful when individual exposure data cannot be obtained. Nonetheless, there may be other workplace exposures associated with the study disease that are not measured in available JEMs. When these exposures are also associated with the exposures measured in the JEM, biases due to uncontrolled confounding will be introduced. Furthermore, individual exposures differ from JEM measurements due to differences in job conditions and worker practices. Uncertainty may also be present at the assessor level since exposure information for each job may be imprecise or incomplete. Assigning individuals a fixed exposure determined by the JEM ignores these uncertainty sources. We examine the uncertainty displayed by bias analyses in a study of occupational electric shocks, occupational magnetic fields, and amyotrophic lateral sclerosis.     

Americans’ Views of Voluntary Protective Actions Against Zika Infection: Conceptual and Measurement Issues

Understanding factors affecting decisions by people to protect themselves, or not, is critical to designing supportive communications. Here, threat, protective‐action, and stakeholder perceptions were evaluated for effects on mainland Americans’ behavioral intentions regarding Zika in April 2017, as postulated by the Protective Action Decision Model. Although all three perception types (including a novel resource sufficiency measure) affected intentions, these relationships varied widely depending upon the method used to measure adoption of actions (e.g., total count of all behaviors adopted vs. behavior‐specific analyses), the behaviors involved, and whether analysis focused on the full sample or only on people who had a reasonable opportunity to enact the behavior or who believed it relevant to their lives. There was a general contrast between mosquito control actions (removal of mosquito breeding areas and pesticide spraying) and travel‐related behaviors (avoiding travel to areas of local transmission of the virus, protecting oneself from mosquito bites after potential exposure, and practicing safe sex after potential exposure). Reported action or inaction during the 2016 mosquito season, and stages of behavior change, were both elicited in January–February 2017; both drove intentions in April 2017 for the upcoming season, although direct and indirect effects varied widely. Collectively these findings present theoretical, measurement, and practical implications for understanding, tracking, and promoting voluntary protective actions against hazards.     

A multicriteria sorting approach based on data envelopment analysis for R&D project selection problem

In this paper, multiple criteria sorting methods based on data envelopment analysis (DEA) are developed to evaluate research and development (R&D) projects. The weight intervals of the criteria are obtained from Interval Analytic Hierarchy Process and employed as the assurance region constraints of models. Based on data envelopment analysis, two threshold estimation models, and five assignment models are developed for sorting. In addition to sorting, these models also provide ranking of the projects. The developed approach and the well-known sorting method UTADIS are applied to a real case study to analyze the R&D projects proposed to a grant program executed by a government funding agency in 2009. A five level R&D project selection criteria hierarchy and an assisting point allocation guide are defined to measure and quantify the performance of the projects. In the case study, the developed methods are observed to be more stable than UTADIS.     

Assessment of Interindividual and Geographic Variability in Human Exposure to Fine Particulate Matter in Environmental Tobacco Smoke

Environmental tobacco smoke (ETS) is a major contributor to indoor human exposures to fine particulate matter of 2.5 μm or smaller (PM_2.5). The Stochastic Human Exposure and Dose Simulation for Particulate Matter (SHEDS‐PM) Model developed by the U.S. Environmental Protection Agency estimates distributions of outdoor and indoor PM_2.5 exposure for a specified population based on ambient concentrations and indoor emissions sources. A critical assessment was conducted of the methodology and data used in SHEDS‐PM for estimation of indoor exposure to ETS. For the residential microenvironment, SHEDS uses a mass‐balance approach, which is comparable to best practices. The default inputs in SHEDS‐PM were reviewed and more recent and extensive data sources were identified. Sensitivity analysis was used to determine which inputs should be prioritized for updating. Data regarding the proportion of smokers and “other smokers” and cigarette emission rate were found to be important. SHEDS‐PM does not currently account for in‐vehicle ETS exposure; however, in‐vehicle ETS‐related PM_2.5 levels can exceed those in residential microenvironments by a factor of 10 or more. Therefore, a mass‐balance‐based methodology for estimating in‐vehicle ETS PM_2.5 concentration is evaluated. Recommendations are made regarding updating of input data and algorithms related to ETS exposure in the SHEDS‐PM model. Interindividual variability for ETS exposure was quantified. Geographic variability in ETS exposure was quantified based on the varying prevalence of smokers in five selected locations in the United States.     

规模不经济下奖惩机制对闭环供应链制造商合作策略影响

存在第三方回收商的闭环供应链中,研究了制造商规模不经情形下,政府奖惩机制对其合作策略的影响。分别构建了制造商仅与零售商（回收商）合作、制造商与零售商和回收商都合作以及均不合作四种合作策略。研究发现：制造商与零售商或回收商均存在合作动机。但是其合作动机的大小则与制造商规模不经济系数及政府奖惩力度有关。若制造商规模不经济系数较小：当政府奖惩力度较小时,制造商倾向与零售商合作;当政府奖惩力度较大时,制造商更倾向与回收商合作;若制造商规模不经济系数较大,制造商总是倾向与回收商合作。此外,无论制造商与零售商或回收商合作总是有利增加旧产品回收总量。     

AEPD、AST和ALD分布下金融资产收益率典型事实描述与VaR度量

金融资产收益率分布具有"尖峰"、"肥尾"、"有偏"、"非对称"等典型事实,传统的正态分布、t分布、SKST分布无法完全描述这些特征,影响了以收益率分布设定为基础之一的参数法VaR模型度量的效果。近年来,理论界提出了AEPD、AST、ALD等分布来改善对金融资产收益率分布的描述。本文以沪深300指数为例,比较和分析了这些分布对金融资产收益率典型事实特征的描述及其在VaR度量效果上的差异。研究表明并非捕捉金融资产收益率分布典型事实越多的模型测度风险的效果越好:AEPD、 AST、ALD分布能较好地描述金融资产收益率的典型特征,但是在风险度量效果上却只能证明AEPD、AST分布绝对优于正态分布,而与SKST分布相比无明显差异; ALD分布在度量空头VaR时效果甚至比正态分布更差,但在计算低分位水平下的多头VaR值时却明显优于其他分布。