求解证券组合最优权重的几何方法

本文通过建立无非负约束和有非负约束条件下证券组合的临界线方程,分别给出了求解允许卖空与限制卖空时证券组合投资最优权重的一种方法。这种方法既可求解给定收益下的证券组合投资最优权重,又可求解给定风险条件下的证券组合投资最优权重。     

投资组合中多目标规划最优化数学模型的应用

本文通过对证券组合投资的预期收益率和投资风险进行综合定量分析,建立了证券组合投资的预期收益率和投资风险进行综合定量分析,建立了证券组合投资的预期收益率和投资风险两个目标均达到最优的多目标规划模型,并对模型进行分析,最后通过案例给出了模型的最优解。     

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。     

一类证券组合投资问题的H∞状态反馈投资策略

为研究兼顾实际系统离散性和参数时变性的证券组合投资问题,提出了一个衡量风险大小的二次型性能指标,并建立了证券组合投资的离散时变状态空间模型.运用离散时变系统的H_∞控制理论,得到了证券组合投资的H_∞状态反馈投资策略.仿真证明使用该投资策略可使总收益实现其最小的不确定性.     

具有资本结构因子和交易成本的证券组合投资模型

在介绍经典的Harry Markowitz均值-方差投资组合模型的基础上,建立了含有资本结构因子和交易成本的证券组合最优化模型,在组合中不含有无风险证券和含有无风险证券的条件下,分别给出最优投资比例及有效边界,并讨论了资本结构因子与交易成本对有效边界的影响.     

一种组合证券选择和资产定价分析

本文研究了参考证券组合对组合证券选择和均衡资产定价的影响。结果表明,对于常用的参考证券组合,相对风险的引入不影响CAPM的成立,但在其他情况下,市场平均的参考证券组合可能成为市场证券组合之外的另一定价状态变量。另一方面,基于绩效的线性报酬结构虽可减少噪声交易造成的损失,但不利于投资管理者充分利用具有价值的信息,并且基于绩效的线性报酬结构无助于激励投资管理者取得超出市场的绩效。     

关于Markowitz投资组合模型的一个注记

本文结合现实生活和实际操作情况,对Ma- rkowitz投资组合模型进行了一定的修正,考虑证券投资买卖证券多少的问题。     

证券组合优化问题探讨

本文讨论了两种证券和三种证券组合优化公式,提出一种比较简单、精确的确定证券投资最佳比例,使证券组合的总风险最小的计算方法。     

ACO算法在投资组合中的运用

证券投资组合优化是降低投资风险的有效方法之一.该文基于现有的相关文献,并将蚂蚁算法引入证券投资组合优化领域,对Markowitz的资产组合模型进行了必要的改进.在对ACO算法作出相应的定义与描述的基础上,文章运用实例检验ACO算法,结果表明该算法具有较好的收敛性、稳定性和合理性,是求解证券投资组合优化问题的一种较好的方法.     

指数证券组合模拟市场指数的聚类和MTV方法

根据Markowitz组合证券投资理论,在一定的假设下,投资者优化其投资组合的结果必定是以市场证券组合为其最优风险资产的投资组合.国外许多研究也表明消极投资策略是有效的,投资者只要按照某个较有代表性的股票市场综合指数中的每个股票所占权重投资每个股票,就可以消除股票的特有风险,达到很好的投资效果.但是,股票市场上股票种类繁多,有限的资金很难按照股票市场综合指数去投资.本文提出了一种利用聚类分析和MTV模型,可以以有限的几种证券的资产组合去逼近市场综合指数的方法.然后以上海股票市场为例,从任意选取的50种股票中使用本方法抽取不超出10种股票,用它们的组合去逼近上证综合指数,取得了比较满意的逼近和预测效果.     

基于投资理论的保险定价公式

在保险公司是风险中性的假设下,运用倒向随机微分方程的理论,研究了保险公司在风险投资框架下的保险定价问题。首先,建立了保险定价问题的线性正倒向随机微分方程数学模型;然后,根据一类特殊线性倒向随机微分方程的显式解,推出了由风险投资确定的保险定价公式;最后,进行了算例分析。     

违约风险、银行信贷筛选与货币政策非对称效应

本文构建一个包含企业违约风险与银行信贷筛选的动态随机一般均衡模型,研究银行信贷筛选对货币政策宏观经济效应产生的影响。在参数校准的基础上,分析了货币政策冲击的长期效应与短期效应。研究结果显示：(1)无论是基于长期还是短期效应的角度,银行信贷筛选均显著抑制了扩张性货币政策对宏观经济产生的积极影响;(2)基于货币政策冲击的短期效应可以发现,银行信贷筛选降低了扩张性货币政策的实际效应,并且放大了货币政策对通胀的影响;(3)通过比较扩张性与紧缩性货币政策的脉冲响应可以发现,银行信贷筛选导致货币政策的宏观经济效应存在非对称性特征。福利分析的结果表明,相比无银行信贷筛选的情形而言,银行信贷筛选导致了整体社会福利的恶化。     

多重不确定环境下基于证据理论的NIS安全风险评估模型

以证据理论为基础,构造一种能够适应多重不确定环境的网络信息系统安全风险评估模型。在模型中建立安全风险评估指标体系并对指标权重进行量化;重新定义基本概率赋值函数,以适应安全风险评估过程中证据的不确定性描述;实现证据一致性检验并确定调整方法,从而进一步降低评估过程中专家经验的不确定性;最后,通过实证分析验证该模型的正确性和有效性。     

IT security planning under uncertainty for high-impact events

While many IT security incidents result in relatively minor operational disruptions or minimal recovery costs, occasionally high-impact security breaches can have catastrophic effects on the firm. Unfortunately, measuring security risk and planning for countermeasures or mitigation is a difficult task. Past research has suggested risk metrics which may be beneficial in understanding and planning for security incidents, but most of these metrics are aimed at identifying expected overall loss and do not directly address the identification of, or planning for, sparse events which might result in high-impact loss. The use of an upper percentile value or some other worst-case measure has been widely discussed in the literature as a means of stochastic optimization, but has not been applied to this decision domain. A key requirement in security planning for any threat scenario, expected or otherwise, is the ability to choose countermeasures optimally with regard to tradeoffs between countermeasure cost and remaining risk. Most of the planning models in the literature are qualitative, and none that we are aware of allow for the optimal determination of these tradeoffs. Therefore, we develop a model for optimally choosing countermeasures to block or mitigate security attacks in the presence of a given threat level profile. We utilize this model to examine scenarios under both expected threat levels and worst-case levels, and develop budget-dependent risk curves. These curves demonstrate the tradeoffs which occur if decision makers divert budgets away from planning for ordinary risk in an effort to mitigate the effects of potential high-impact outcomes.     

资本监管标准与金融安全机理探讨

资本作为一种风险缓冲剂,具有承担风险、吸收损失、保护银行抵御意外冲击的作用,是保障银行安全的最后一道防线,实施资本监管是保证金融安全的主要手段。本文运用数学模型分析工具,从金融安全的角度对金融业资本监管进行了分析,得出了合乎逻辑的理论结论,为实践中的运用提供了理论基础。本文的研究在于丰富金融监管理论文献的同时,也为指导我国金融业今后的发展提出了重要的理论证据。     

定期信用支付条件下的多阶段货价变动型存贮问题

本文研究了定期信用支付条件下的多阶段货价变动型存贮问题,得到了最优订购策略并设计了算法以说明模型的使用。     

做市商制度下证券价格的形成机制分析

证券价格的形成要受到交易机制的约束,也会受到投资者的风险偏好、信念以及对信息获知程度的影响.文章将把这两方面因素结合起来考虑,把信息不对称引入模型,对做市商市场的证券价格形成机制进行了均衡分析.结果表明,一方面,在存在做市商的证券市场,投资者根据自己的风险偏好、信念和获知信息进行交易以使预期效用最大化,交易指令的下达与执行传达了证券清算价值的信息.做市商通过对指令信息的观察而进行双向报价,为市场提供了流动性;另一方面,证券市场的有序运行不仅跟交易机制有关,还受到投资者的风险偏好、信念以及信息上的差异等的影响,这也是决定证券价格的关键因素.     

AbSRiM: An Agent‐Based Security Risk Management Approach for Airport Operations

Security risk management is essential for ensuring effective airport operations. This article introduces AbSRiM, a novel agent‐based modeling and simulation approach to perform security risk management for airport operations that uses formal sociotechnical models that include temporal and spatial aspects. The approach contains four main steps: scope selection, agent‐based model definition, risk assessment, and risk mitigation. The approach is based on traditional security risk management methodologies, but uses agent‐based modeling and Monte Carlo simulation at its core. Agent‐based modeling is used to model threat scenarios, and Monte Carlo simulations are then performed with this model to estimate security risks. The use of the AbSRiM approach is demonstrated with an illustrative case study. This case study includes a threat scenario in which an adversary attacks an airport terminal with an improvised explosive device. The approach provides a promising way to include important elements, such as human aspects and spatiotemporal aspects, in the assessment of risk. More research is still needed to better identify the strengths and weaknesses of the AbSRiM approach in different case studies, but results demonstrate the feasibility of the approach and its potential.     

Use of Fuzzy Evidential Reasoning in Maritime Security Assessment

Over the last few years, there has been a growing international recognition that the security performance of the maritime industry needs to be reviewed on an urgent basis. A large number of optional maritime security control measures have been proposed through various regulations and publications in the post-9/11 era. There is a strong need for a sound and generic methodology, which is capable of taking into account multiple selection criteria such as the cost effectiveness of the measures based on reasonable security assessment. The use of traditional risk assessment and decision-making approaches to deal with potential terrorism threats in a maritime security area reveals two major challenges. They are lack of capability of analyzing security in situations of high-level uncertainty and lack of capability of processing diverse data in a utility form suitable as input to a risk inference mechanism. To deal with such difficulties, this article proposes a subjective security-based assessment and management framework using fuzzy evidential reasoning (ER) approaches. Consequently, the framework can be used to assemble and process subjective risk assessment information on different aspects of a maritime transport system from multiple experts in a systematic way. Outputs of this model can also provide decisionmakers with a transparent tool to evaluate maritime security policy options for a specific scenario in a cost-effective manner.