A Multi-Objective Genetic Algorithm for Optimal Portfolio Problems

This paper concerns with modeling and design of an algorithm for the portfolio selection problems with fixed transaction costs and minimum transaction lots. A mean-variance model for the portfolio selection problem is proposed, and the model is formulated as a non-smooth and nonlinear integer programming problem with multiple objective functions. As it has been proven that finding a feasible solution to the problem only is already NP-hard, based on NSGA-II and genetic algorithm for numerical optimization of constrained problems (Genocop), a multi-objective genetic algorithm (MOGA) is designed to solve the model. Its features comprise integer encoding and corresponding operators, and special treatment of constraints conditions. It is illustrated via a numerical example that the genetic algorithm can efficiently solve portfolio selection models proposed in this paper.This approach offers promise for the portfolio problems in practice.     

Multi-period model of portfolio investment and adjustment based on hybrid genetic algorithm

This paper proposes a multi-period portfolio investment model with class constraints, transaction cost, and indivisible securities. When an investor joins the securities market for the first time, he should decide on portfolio investment based on the practical conditions of securities market. In addition, investors should adjust the portfolio according to market changes, changing or not changing the category of risky securities. Markowitz mean-variance approach is applied to the multi-period portfolio selection problems. Because the sub-models are optimal mixed integer program, whose objective function is not unimodal and feasible set is with a particular structure, traditional optimization method usually fails to find a globally optimal solution. So this paper employs the hybrid genetic algorithm to solve the problem. Investment policies that accord with finance market and are easy to operate for investors are put forward with an illustration of application.     

Matrix decomposition and Lagrangian dual method for discrete portfolio optimization under concave transaction costs

In this paper, the discrete mean-variance model is considered for portfolio selection under concave transaction costs. By using the Cholesky decomposition technique, the convariance matrix to obtain a separable mixed integer nonlinear optimization problem is decomposed. A brand-and-bound algorithm based on Lagrangian relaxation is then proposed. Com-putational results are reported for test problems with the data randomly generated and those from the US stock market.     

离散多因素投资组合最优化模型的分枝定界算法

In this paper, a new branch-and-bound algorithm based on the Lagrangian dual relaxation and continuous relaxation is proposed for discrete multi-factor portfolio selection model with roundlot restriction in financial optimization. This discrete portfolio model is of integer quadratic programming problems. The separable structure of the model is investigated by using Lagrangian relaxation and dual search. Computational results show that the algorithm is capable of solving real-world portfolio problems with data from US stock market and randomly generated test problems with up to 120 securities.     

财产保险公司投资组合问题的多阶段随机规划模型

财产保险公司的投资组合模型均是单期的 ,不能充分满足投资组合管理实践的需要 .为提供多期规划工具 ,建立了一个多阶段的随机规划模型 .它考虑了交易成本 ,分析了不同时期的现金流 ,讨论了资产负债的匹配问题 ,去掉了收益分布的正态假定 ,并增加了一种投资约束 .数值实例的计算结果表明 ,多期模型能更好地帮助财产保险公司选择保险与投资的优化组合 ,其性能要优于单期模型     

几种多目标证券投资组合模型的比较研究

马科维茨提出的投资组合模型是单目标二次规划模型，具有重要的理论意义。参考文献[3]给出一种多目标词不达意投资组合决策模型。文章依据不同的投资者的个人偏好，给出了几种具有可操作性的多目标规划模型，并对它们的性质进行了简单比较，提出了一种模糊目标函数模型。     

Portfolios and assessment in teacher education in Norway: a theory‐based discussion of different models in two sites

Two teacher institutions in Norway involved in a new ICT‐supported portfolio project provide data for our study. In this paper we present a model of analysis for portfolio processes based on sociocultural perspectives of learning and assessment and describe and discuss differences and similarities of the portfolio models in these institutions in relation to our model of analysis. We also highlight areas for improvement; among them the importance of building reflection, self‐assessment and feedback into portfolio assignments and processes in such a way that it becomes part of what is documented. This will strengthen the formative assessment aspect of portfolios. The summative assessment practices are strongly influenced by exam traditions in both institutions. Digital portfolios provide new learning opportunities that are not yet fully utilized. By way of conclusion we explore some critical aspects of portfolios in teacher education in light of Wenger's social theory of learning, focusing on the concepts participation, reification and identity formation.     

基于递归神经网络的证券组合投资

对神经网络在评券投资管理三个阶段 :变量选择、收益预测、证券组合方面的应用进行了分析 .在此基础上 ,着重对不允许卖空情况下预期收益固定、风险最小的证券最优组合的投资比例系数的求解提出了一种确定性模拟退火神经网络的解法 .最后 ,通过实例验证了模型的有效性     

一类投资组合模型的模糊两阶段算法

对多目标证券组合投资模型进行了研究，模型以风险损失率作为风险。该模型是一多目标线性优化问题．我们采用模糊折衷算法对模型进行了求解，算例给出了该模型的一个实例的最优解。     

存在无风险资产的M-V有效前沿进一步研究

在均值-方差证券选择理论的基础上,引入扰动因子对增加证券数目后原有证券组合间相关性的改变进行了描述,运用代数运算简化模型推导,分析了在市场存在无风险证券且允许卖空条件下受扰动的M-V有效前沿,并且得出了有效前沿发生漂移的结论.为投资者及其投资决策提供了基本的方法和有意义的思路.     

The Introduction of Portfolios in Higher Education: a comparative study in the UK and the Netherlands

This article describes a comparative study of the introduction of student portfolios in two departments of the Vrije Universiteit Amsterdam in the Netherlands and Nottingham Trent University in the UK. Portfolios are designed to facilitate effective management of lifelong learning, to provide a record of achievements and to encourage self-reflection by students.
The justifications for the portfolio initiative are different in the two countries. At the Vrije Universiteit, the initiative arose within the University but is being implemented by individual faculties. There is no standard model of implementation. At Nottingham Trent University, portfolios are being introduced as a response to a government directive, as part of a lifelong learning portfolio that each individual will carry forward into their working life. The University's response to this imperative is top-down and a University-wide model is being sought. The department model is one of several models that are being evaluated for this purpose.
This research project investigates whether these alternative starting points lead to differential responses from student users or not. Data are drawn from quantitative (questionnaires) and qualitative (interviews with managers, consultants and teachers) sources. Similarities and differences in students' responses to the portfolio exercise are identified and discussed in terms of factors such as the way the portfolios are introduced, the incentives offered to complete them, the role of the lecturer and peers in the monitoring of study progress, the quality of self-regulative skills, and students' learning expectations.     

连续时间两资产模型的最优方程

研究了在连续时间两资产模型中个人最优投资组合选择与消费准则的结合问题,采用由离散时间模型过渡到连续时间极限情形的方法,给出了动态预算方程.在收益率由Wiener Brown运动过程生成的条件下,推导出了两资产问题的最优方程.     

组合投资问题的目标规划模型及其求解

引入非凹非凸的典型交易成本函数形式，考虑分红收益提出含有典型交易成本的组合投资问题的目标规划模型，通过实例对模型中无交易成本、含有V-型交易成本、典型交易成本时所得的有效前沿进行比较，并分析了不同期望收益水平对投资组合的影响．     

动态环境模糊投资组合模型求解

基于模糊集及模糊区间的概念,提出一种动态环境模糊投资组合模型。设计的重点为:(1)投资资产的收益率设计为区间模糊数;(2)风险率设计为三角模糊数。将建立的模糊投资组合模型转化为清晰数学规划问题,并将免疫优化算法对模型求解,数值实验中选取历史数据,将Lindo软件求解结果与免疫算法求解结果比较,充分表明免疫算法对模糊投资组合模型求解的有效性。     

中国区域农业竞争力评价及分析——基于组合赋权法的模糊综合评价模型

在回顾组合赋权法以及模糊综合评价模型的基础上,选取我国2011年农业竞争力的四大要素11项指标数据,对我国27个省、自治区的农业竞争力进行基于组合赋权法的模糊综合评价分析,之后对各省利用模糊C聚类进行聚类分析,以此来评判我国区域农业竞争力。结果表明：组合赋权法更具有科学性,农业经营主体竞争力和农业生产要素条件所占权重更大;各省农业发展综合水平具有明显的不均衡性,各省农业发展综合水平具有显著的区域性;各类省份的农业竞争力四大要素各有优劣,都有提升空间。最后根据分析结果得出的一些结论及政策建议。     

风险修正下的证券组合选择模型

对投资对象进行了选择,提出了投资对象选择模型,并研究了在投资对象选择模型下组合证券的有效边界,发现其有效边界是由N种投资对象选择模型的有效边界上的点组成的抛物线段。     

Changes in secondary teachers' perceptions of barriers to portfolio assessment

Portfolio assessment has become a popular medium for merging classroom assessment with large-scale testing, but adoption of portfolios in the classroom for external assessment purposes may be difficult because the use of such portfolios may require changes in the curriculum, instructions, and assessments used by teachers. As a result, there are numerous potential barriers to the adoption of portfolios that can be used for large-scale assessment purposes. This study investigates how secondary teachers' perceptions of portfolio implementation barriers changed when teachers participated in a 1-year portfolio implementation effort. Survey results are analyzed with a Rasch rating scale model. Results suggest that teachers' apprehension about portfolio barriers increased slightly, but that this increase can be attributable to teachers with little portfolio experience. Furthermore, teachers' concerns about the amount of time required to develop and score portfolios increased substantially while concerns about the availability of resources and resistance from parents decreased.     

Developing and validating a design for teacher portfolio assessment

Developing and using a design for teacher portfolio assessment is a complex process including several components: the domain to be assessed (the teacher competences), the content standards or criteria, the portfolio format, the completion of the format (by teachers) with content, and the scoring of the portfolios (by raters). For a portfolio assessment to be valid, these components should be systematically linked. Using a chain model of the assessment process two links were verified: the link between content standards and portfolio format, and the link between content standards and raters’ scoring. Eight experts evaluated an initial portfolio assessment design. They greatly supported the design, including the link between standards and format. Subsequently, using the format 18 teachers developed a portfolio. Six raters scored these portfolios according to eight content standards. Their scoring was substantially based on the content standards. Implications of the results and suggestions for research are discussed.     

损失规避下的指数跟踪问题及其粒子群算法求解

随着指数衍生产品日益受到重视,指数化投资组合常被传统的消极基金管理者或机构所采用,而用有限的资金按指数构成比例进行投资显然是不现实的,所以指数的最优误差追踪就显得更加重要。将追踪误差定义为证券投资组合收益率与所追踪的指数基准收益率之差的均值平方和的平方根,建立了基数约束（即总资产数不超过某个特定整数K）下考虑投资者损失规避决策偏好的跟踪误差最小化模型,并设计了一个粒子群算法求解模型。实际算例表明,所构建的模型和算法是有效的。     

遗传算法在我国证券市场中的应用

分析我国证券市场现状的基础上,根据不允许卖空、并考虑交易成本的情况下,建立了多因素证券组合投资决策模型,然后利用遗传算法研究了模型的求解,进行了实证研究。