基于CAR模型国内A股市场反应不足的实证分析

主要关注的主体异象为反应不足,在已有的HS模型基础上,对我国IPO改革背景下的证券市场投资策略进行了实证研究.实证过程中主要采用了市场调整模型计算累计超额收益率,并根据样本条件划分适当的形成期和检验期.在此基础上,以经典的"赢者组合"和"输者组合"方法对实证数据进行分析,最终发现A股市场中存在反应不足的金融异象.     

基于遗传算法证券市场违规交易数据智能搜索

通过对我国证券市场中的内幕交易"老鼠仓"问题的研究,力图设计一个基于遗传算法的证券内幕交易异常数据自动检索系统,用来监控股票的违规操作.系统通过将遗传算法的快速搜索与异常处理判断模块结合,对出现异常波动的股票进行实时行情数据的跟踪、分析与调查,从中找出异常数据.之后再对这些异常数据进行比较和判断,定位该股是否具有违规的"老鼠仓"交易嫌疑,以此为证监部门判断某股是否有"老鼠仓"嫌疑提供依据.     

离散约束条件下的实用投资组合选择模型

鉴于现实证券市场中的投资会受到很多类型的约束的限制,本文在同时综合反映多种市场摩擦与恰当度量投资风险的原则下,构建了两种分别以CVaR和双边一致性度量为风险度量的离散型多重约束实用投资组合选择模型。基于深圳证券交易所A股的日交易数据,我们从实证角度着重考虑了交易费用约束与逻辑约束对最优投资策略选择及其性能的影响,并给出了一些实用的投资建议。实证结果表明:新模型不仅可行、有效,而且能合理反映不同市场摩擦的作用。     

中国证券市场知情交易概率的动态马尔科夫状态转移模型研究

对指令驱动市场知情交易的研究是近年来的热点问题。常用的EKOP模型存在一些缺陷,本文放宽了EKOP模型关于日内信息均匀释放以及交易者行为独立性的假设,用动态的马尔科夫状态转移模型对该模型进行了改进,并检验了改进后的知情交易概率模型在中国证券市场的适用性。通过模拟数据以及对中国证券市场交易数据的实证研究发现动态的马尔科夫状态转移模型克服了EKOP模型受买卖方数据影响而产生的系统偏误,估计的知情交易概率更符合事后检验。     

离散单因素投资组合模型的对偶算法

本文研究金融优化中的离散单因素投资组合问题,该问题与传统投资组合模型的不同之处是决策变量为整数(交易手数),从而导致要求解一个二次整数规划问题．针对该模型的可分离性结构,我们提出了一种基于拉格朗日对偶和连续松弛的分枝定界算法。我们分别用美国股票市场的交易数据和随机产生的数据对算法进行了测试．数值结果表明该算法是有效的,可以求解多达150个风险证券的离散投资组合问题．     

基于模糊决策的投资组合优化

基于模糊决策理论研究了带有成比例交易费用的证券投资组合优化问题. 首先,基于半绝对偏差风险函数和极大极小原则提出了一种新的风险函数--极大极小半绝对偏差风险函数;然后, 引入一种非线性隶属函数更加形象地描述了投资者对投资收益和投资风险的满意程度;在此基础上, 进一步提出了非线性满意程度的模糊决策投资组合选择模型;最后, 针对提出的模型,利用中国证券市场的真实数据给出了数值算例.     

求解带有交易费的CVaR投资组合模型的L-S算法

本文假设投资者是风险厌恶型,用CVaR作为测量投资组合风险的方法.在预算约束的条件下,以最小化CVaR为目标函数,建立了带有交易费用的投资组合模型.将模型转化为两阶段补偿随机优化模型,构造了求解模型的随机L-S算法.为了验证算法的有效性,用中国证券市场中的股票进行数值试验,得到了最优投资组合、VaR和CVaR的值.而且对比分析了有交易费和没有交易费的最优投资组合的不同,给出了相应的有效前沿.     

离散线性投资组合模型的分枝定界算法

本文提出了一类新的带整数交易手数和凹型交易费用的均值绝对偏差模型(MAD)和极大极小投资组合模型(Minmax),并给出了离散模型的分枝定界算法.我们分别用随机产生的数据和Nasdaq股票市场的真实数据进行了数值实验,数值分析表明在一定的收益水平下均值绝对偏差离散模型风险控制上优于极大极小投资组合离散模型,而计算效率上极大极小投资组合离散模型优于期望绝对偏差离散模型.     

基于BAPM模型的噪声交易者风险的测度——以受处罚的上市公司为例研究

过度的噪音交易,尤其是受到行政处罚的上市的噪声交易,在我国证券市场是非常普遍的。选用2007～2009年内受到中国证监会行政处罚的上市公司,从2006年1月到2009年12月的收益率作为分析的样本,同时取其对应的同行业的配对公司进行实证研究得出结论,噪声交易者风险(NTR)与股票超额收益是显著负相关的,显著性越高,那么投资者投资此类股票受到损失的可能性越大。最后,本文提出了治理我国股市噪声问题、提高市场有效性的政策建议。     

考虑完整交易费用的组合证券投资求解

针对中国证券市场现存的各种交易费用,建立一个更加符合实际的组合证券投资模型.该模型不仅继承了股票不可拆分、不能卖空等特点,而且完全反映了交易费用的核算情况;最后给出一个遗传算法结合动态罚函数求解的投资实例,计算结果证明了该模型及其求解方法的有效性和可操作性.     

Use of DEA cross-efficiency evaluation in portfolio selection: An application to Korean stock market

We propose a way of using DEA cross-efficiency evaluation in portfolio selection. While cross efficiency is an approach developed for peer evaluation, we improve its use in portfolio selection. In addition to (average) cross-efficiency scores, we suggest to examine the variations of cross-efficiencies, and to incorporate two statistics of cross-efficiencies into the mean-variance formulation of portfolio selection. Two benefits are attained by our proposed approach. One is selection of portfolios well-diversified in terms of their performance on multiple evaluation criteria, and the other is alleviation of the so-called “ganging together” phenomenon of DEA cross-efficiency evaluation in portfolio selection. We apply the proposed approach to stock portfolio selection in the Korean stock market, and demonstrate that the proposed approach can be a promising tool for stock portfolio selection by showing that the selected portfolio yields higher risk-adjusted returns than other benchmark portfolios for a 9-year sample period from 2002 to 2011.     

基于展望理论的证券市场反应过度和反应不足研究

本文以KT(1979)的展望理论和过度自信、自我归因心理偏差为基础,建立了解释反应过度和反应不足异常现象的投资心理展望价值模型,研究了股票市场上反应不足和反应过度异常现象形成的机理,并解释了我国股票市场中反应不足和反应过度的一些具体特征。     

Stochastic Nonstationary Optimization for Finding Universal Portfolios

We apply ideas from stochastic optimization for defining universal portfolios. Universal portfolios are that class of portfolios which are constructed directly from the available observations of the stocks behavior without any assumptions about their statistical properties. Cover [7] has shown that one can construct such portfolio using only observations of the past stock prices which generates the same asymptotic wealth growth as the best constant rebalanced portfolio which is constructed with the full knowledge of the future stock market behavior.In this paper we construct universal portfolios using a different set of ideas drawn from nonstationary stochastic optimization. Our portfolios yield the same asymptotic growth of wealth as the best constant rebalanced portfolio constructed with the perfect knowledge of the future and they are less demanding computationally compared to previously known universal portfolios. We also present computational evidence using New York Stock Exchange data which shows, among other things, superior performance of portfolios which explicitly take into account possible nonstationary market behavior.     

The geometry of relative arbitrage

Consider an equity market with n stocks. The vector of proportions of the total market capitalizations that belong to each stock is called the market weight. The market weight defines the market portfolio which is a buy-and-hold portfolio representing the performance of the entire stock market. Consider a function that assigns a portfolio vector to each possible value of the market weight, and we perform self-financing trading using this portfolio function. We study the problem of characterizing functions such that the resulting portfolio will outperform the market portfolio in the long run under the conditions of diversity and sufficient volatility. No other assumption on the future behavior of stock prices is made. We prove that the only solutions are functionally generated portfolios in the sense of Fernholz. A second characterization is given as the optimal maps of a remarkable optimal transport problem. Both characterizations follow from a novel property of portfolios called multiplicative cyclical monotonicity.     

基于几种风险测度的多阶段组合优化研究

基于均值-方差(MV)、VaR(Value at Risk)、CVaR(Conditional VaR)、HMCR(p=1,2,3)(Higher Moment Coherent Risk)几种风险测度进行多阶段组合优化研究。首先从一致性公理和随机占优一致性角度分析几种风险测度的风险识别能力,认为HMCR(p=2,3)的风险识别能力最高,然后给出静态和动态下的风险规避型的规划函数及多阶段CVaR和HMCR模型,最后依据单阶段和多阶段优化模型,对上证50指数成份股进行实证分析。对比单阶段和多阶段下几种风险测度优化组合的累计收益率及几种风险测度之间的关系,结合上证50指数收益率发现,多阶段优化组合要整体优于单阶段优化组合,且HMCR(p=2,3)要优于指数收益率和其它几种风险测度。从投资者投资决策方面来分析,HMCR(p=2,3)型积极投资策略比较适用于股市平稳期、顶峰期和下降期,被动投资策略比较适用于股市上升期。     

投资者过度反应与牛熊市波动非对称性

论文针对沪深股市牛熊市中所呈现出的波动非对称性的差异,从牛熊市中投资者对信息反应的差异角度予以解释。论文以非预期交易量变化率作为投资者对信息冲击反应的代理变量,研究显示投资者在牛市行情中的过度反应,是造成沪深股市牛市行情波动正向非对称性的重要原因。与此同时论文通过对比美国、香港和沪深股市上牛熊市波动非对称性差异,进一步验证沪深市场上不完善的市场机制加剧了投资者在牛市行情中的过度反应,进而导致牛市行情中的波动正向非对称性。     

不同风险度量约束下带有红利的投资组合模型研究

对现有的在风险度量约束下的投资组合模型进行了推广.建立了带有红利情形的随机股票市场模型,给出了投资组合关于这些风险度量约束下的最优化结果.     

A general approach to Bayesian portfolio optimization

We develop a general approach to portfolio optimization taking account of estimation risk and stylized facts of empirical finance. This is done within a Bayesian framework. The approximation of the posterior distribution of the unknown model parameters is based on a parallel tempering algorithm. The portfolio optimization is done using the first two moments of the predictive discrete asset return distribution. For illustration purposes we apply our method to empirical stock market data where daily asset log-returns are assumed to follow an orthogonal MGARCH process with t-distributed perturbations. Our results are compared with other portfolios suggested by popular optimization strategies.     

Efficient portfolios in financial markets with proportional transaction costs

In this article, we characterize efficient portfolios, i.e. portfolios which are optimal for at least one rational agent, in a very general multi-currency financial market model with proportional transaction costs. In our setting, transaction costs may be random, time-dependent, have jumps and the preferences of the agents are modeled by multivariate expected utility functions. We provide a complete characterization of efficient portfolios, generalizing earlier results of Dybvig (Rev Financ Stud 1:67–88, 1988) and Jouini and Kallal (J Econ Theory 66: 178–197, 1995). We basically show that a portfolio is efficient if and only if it is cyclically anticomonotonic with respect to at least one consistent price system that prices it. Finally, we introduce the notion of utility price of a given contingent claim as the minimal amount of a given initial portfolio allowing any agent to reach the claim by trading, and give a dual representation of it as the largest proportion of the market price necessary for all agents to reach the same expected utility level.     

“CA结构的智能Agent”方法的构建与应用

智能体和元胞自动机是基于复杂适应系统理论(CAS)框架下应用较成熟的两种行为模拟方法,在对它们的优缺点及适用领域进行比较分析的基础上,构建了一种更适合人类复杂行为模拟的新方法——"CA结构的智能Agent".并将其应用于股市投资者行为的模拟研究中,模拟结果验证了股市投资行为中的羊群行为和复杂系统特性.此外,模拟还发现股市达到均衡的时间和状态取决于投资者的类型和比例.