中国证券投资基金对股市影响研究

 以1998年3月底金泰、开元两只具有真正意义上的证券投资基金的设立为标志,我国基金业进入了规范发展时期,政府在给予其积极政策扶持的同时,也对其稳定股市的功能寄予了厚望。但在实践中,证券投资基金对股市的影响却引来了不同的争议。本文试从基金所持货币资产比例、基金股票持有期限及基金股票差价收益与股息收益的比例三个方面来分析证券投资基金对股市的实际影响,并在挖掘造成这种结果的深层次内部和外部原因基础上提出对策建议。     

证券投资基金经营业绩评价研究与其实证分析

一、问题的提出随着金融技术、市场与制度日新月异的创新、生产费用及机会成本的降低 ,高节奏高效率的基金业得以快速壮大 ,并从其他金融业脱颖而出 ,从而成为名副其实的金融业的高新技术产业。国外半个世纪的实践已经证明 ,基金业所创造的生产力 ,大大超乎人们的想象力 ,从造就繁荣和稳定市场的角度上 ,其意义已远远高于银行业和证券业。从国外证券市场上的实践经验来看 ,基金业取得了显著的投资成效。我国证券市场从无到有 ,近 1 0年的风风雨雨走过了国外上百年的发展历程。但正如国外证券市场发展已经证明的 ,基金业的发展对于一个国家资…     

论统计平均法在证券技术分析中的应用

 平均法是统计分析方法的核心,是统计学的基础和精髓,是大数定律统计思想的极好体现,也是证券技术分析领域中应用最为广泛的统计方法。尽管各种证券技术分析方法丰富多彩,令人眼花缭乱,但平均法却始终发挥着最重要的作用。     

Bootstrap方法在证券投资基金风险测量中的应用

 Bootstrap method will largely improve the accuracy of risk measurement, which be used to calculate the value at risk of securities investment funds. The application of the Bootstrap method with GARCH-based risk measurement model, not only consider the fund’s data auto-correlation and the time-variable variance characteristic, but also very well simulate the distribution of the residual. The theoretical analysis and empirical analysis indicate that this flexible parameter-nonparametric mixed risk measurement model can improve estimation precision of VAR.     

资产分配的策略比较分析

一、引言随着我国证券市场的不断发展 ,机构投资者的队伍也迅速壮大 ,这种趋势对市场微观结构的明显影响就是组合管理策略显得越发重要。组合管理的核心之一就是资产分配 (ＡｓｓｅｔＡｌｌｏｃａｔｉｏｎ)比例的制定。机构投资者的资产分配通常由两部分构成 :( 1)政策性约束导致的被动分配 ,如我国《证券投资基金管理暂行办法》第五章第三十三条就明确规定 :一家基金投资于股票、债券的比例 ,不得低于该基金资产总值的 80 % ;一家基金投资于国家债券的比例 ,不得低于该基金资产净值的 2 0 % ;( 2 )积极的资产分配。一个正确的资产分配策略 …     

组合证券投资风险最小化模型研究

组合证券投资风险最小化模型研究①杨桂元马永开唐小我ＡＢＳＴＲＡＣＴ①国家教委优秀年轻教师基金资助项目。ＢａｓｅｄｏｎｇｅｎｅｒａｌＭｉｎｉｍｉｚｅｄＲｉｓｋＭｏｄｅｌｏｆＣｏｍｂｉｎｅｄＳｅｃｕｒｉｔｉｅｓｉｎｖｅｓｔｍｅｎｔ,ｔｈｅａｕｔｈｏｒｓｓ...     

量化分析与模糊量化分析的比较研究

本文对量化分析和模糊量化分析的异国进行比较。限于篇幅,这里仅讨论量化分析和模糊量化分析的第1,2类。     

直接消耗系数变动的比较分析

一、引言自从Ｗ．Ｌｅｏｎｔｉｅｆ提出投入产出技术以来,投入产出技术在分析经济问题时取得了很大的成功。由于投入产出表的编制及出版一般要滞后于编表年份大约５年左右,并且,投入产出技术的两个基本假定（比例性假定和同质性假定）以及用于实际预测时常假定直接消耗...     

对国际经济比较方法的若干思考

对国际经济比较方法的若干思考邱东ＡＢＳＴＲＡＣＴＴｈｅｍｅｔｈｏｄｏｆｅｘｃｈａｎｇｅｒａｔｅｈａｓｇｒａｄｕａｌｙｌｏｓｔｉｔｓｌｅａｄｉｎｇｒｏｌｅｉｎｉｎｔｅｒｎａｔｉｏｎａｌｃｏｍｐａｒｉｓｏｎｂｅｃａｕｓｅｏｆＩＣＰ（Ｉｎｔｅｒｎａｔｉｏｎ...     

关于国民经济账户和政府财政账户的比较分析

ＧＤＰ(国内生产总值)是国民经济核算体系中的核心指标,它被用来计算国民经济增长速度,衡量一个国家或地区的经济发展水平,分析和评价经济发展的态势,有时甚至用于考核地方政府工作的政绩,成了政府官员、经济学家、社会学家、统计学家言必谈的指标。由于ＧＤＰ是侧重于经济方面核算的总量指标,没有充分考虑资源与环境因素,随着可持续发展战略的实施,资源环境经济之间协调发展提到议事日程。为此,理论界提出了清洁生产、绿化ＧＤＰ,这样绿色ＧＤＰ(绿色国内生产总值)的测算尤显重要。　　一、ＧＤＰ绿化和绿色ＧＤＰＧＤＰ绿化是指针对ＧＤＰ…     

合理投资率的实证分析

 合理的投资率（又称积累率）一直是世界各国经济学家关心的问题。包括美国在内的许多发达国家经济学家们担心由于这些国家的投资率太低,经济增长缺乏后劲。我国许多经济学家们则担心由于我国投资率太高,最终消费率太低而降低投资率,是投资者失去投资信心。因此,如果能确定一个合理的投资率,并将一国的投资与消费比例控制在这一水平上,对经济的可持续发张无疑是有益的。本文从理论上分析了经济增长与投资率、投资乘数、投资增长率的明确关系,并用包括我国在内的五国统计资料对这一关系进行了实证分析,在此基础上系统分析了我们合理投资率问题。     

基于2007年投入产出表的我国投资乘数测算和变动分析

 本文对固定资产投资乘数、凯恩斯投资乘数和投入产出投资乘数等三种投资乘数进行了测算分析,结果表明近年来我国投资乘数并没有发生大幅度下降,对经济增长的拉动贡献较大。通过对4万亿投资计划的具体测算,表明投资对拉动内需和抵御外部冲击发挥了巨大作用。作为发展中国家,保持较高的投资增速是经济可持续发展的必要条件,未来投资仍将是拉动我国经济增长的主要动力。但应当积极调整投资结构,避免产能过剩、抑制房地产价格上涨,提高投资效率。     

Comparative analysis of modern optimization tools for the p-median problem

This paper develops a study on different modern optimization techniques to solve the p-median problem. We analyze the behavior of a class of evolutionary algorithm (EA) known as cellular EA (cEA), and compare it against a tailored neural network model and against a canonical genetic algorithm for optimization of the p-median problem. We also compare against existing approaches including variable neighborhood search and parallel scatter search, and show their relative performances on a large set of problem instances. Our conclusions state the advantages of using a cEA: wide applicability, low implementation effort and high accuracy. In addition, the neural network model shows up as being the more accurate tool at the price of a narrow applicability and larger customization effort.     

高科技公司投资价值信息识别的实证研究

一、研究背景高科技公司具有高风险、高回报、高成长的特性 ,因此投资风险较大。面临快速的环境变迁和风险变化 ,投资者如何分析和判断高科技公司未来的增长潜力和投资价值 ,己经成为投资决策的重要问题。投资风险是指投资者对高科技公司各个不同发展时期内在真实价值的估算偏差。目前西方学者的理论研究及企业的实践经验表明 ,由于投资者与高科技公司存在严重的信息不对称 ,投资者事实上承担了企业很大一部分的投资风险。因此 ,投资者需要对高科技企业投资价值信息进行全面的识别、筛选和监控 ,通过建立一种信息识别模式 ,正确地反映并评价…     

Sub-optimal investment for insurers

Abstract

We consider the investment problem for a non-life insurance company seeking to minimize the ruin probability. Its reserve is described by a perturbed risk process possibly correlated with the financial market. Assuming exponential claim size, the Hamilton-Jacobi-Bellman equation reduces to a first order nonlinear ordinary differential equation, which seems hard to solve explicitly. We study the qualitative behavior of its solution and determine the Cramér-Lundberg approximation. Moreover, our approach enables to find very naturally that the optimal investment strategy is not constant. Then, we analyze how much the company looses by adopting sub-optimal constant (amount) investment strategies.     

Using a genetic algorithm-based RAROC model for the performance and persistence of the funds

Assisting fund investors in making better investment decisions when faced with market climate change is an important subject. For this purpose, we adopt a genetic algorithm (GA) to search for an optimal decay factor for an exponential weighted moving average model, which is used to calculate the value at risk combined with risk-adjusted return on capital (RAROC). We then propose a GA-based RAROC model. Next, using the model we find the optimal decay factor and investigate the performance and persistence of 31 Taiwanese open-end equity mutual funds over the period from November 2006 to October 2009, divided into three periods: November 2006–October 2007, November 2007–October 2008, and November 2008–October 2009, which includes the global financial crisis. We find that for three periods, the optimal decay factors are 0.999, 0.951, and 0.990, respectively. The rankings of funds between bull and bear markets are quite different. Moreover, the proposed model improves performance persistence. That is, a fund's past performance will continue into the future.     

Multiple tests for the performance of different investment strategies

In the context of modern portfolio theory, we compare the out-of-sample performance of eight investment strategies which are based on statistical methods with the out-of-sample performance of a family of trivial strategies. A?wide range of approaches is considered in this work, including the traditional sample-based approach, several minimum-variance techniques, a shrinkage, and a minimax approach. In contrast to similar studies in the literature, we also consider short-selling constraints and a risk-free asset. We provide a way to extend the concept of minimum-variance strategies in the context of short-selling constraints. A main drawback of most empirical studies on that topic is the use of simple testing procedures which do not account for the effects of multiple testing. For that reason we conduct several hypothesis tests which are proposed in the multiple-testing literature. We test whether it is possible to beat a trivial strategy by at least one of the non-trivial strategies, whether the trivial strategy is better than every non-trivial strategy, and which of the non-trivial strategies is significantly outperformed by naive diversification. The empirical part of our study is conducted using US stock returns from the last four decades, obtained via the CRSP database.