高频数据下积分波动率矩阵的伪似然估计、预测及应用

研究目标:利用高频数据准确估计和预测高维积分波动率矩阵,并将矩阵的预测值应用于资产投资组合的构造中。研究方法:通过保留p×p维已实现波动率矩阵的特征向量,对积分波动率矩阵的特征值进行预测,本文将积分波动率矩阵的估计和预测问题转化为p个一维积分波动率的估计和预测问题。研究发现:对高维已实现波动率矩阵过于发散的特征值进行调整能够提高矩阵估计的准确性;对资产收益率的积分波动率矩阵建立动态模型可以提高矩阵预测的精度。研究创新:将高维矩阵的估计和预测问题转化为矩阵特征向量的估计以及一维特征值的估计和预测问题;基于高频数据并建立资产收益率积分波动率矩阵的动态模型提高了资产投资组合的样本外表现。研究价值:本文提出的积分波动率矩阵估计和预测方法能够保证矩阵估计值和预测值的正定性;本文的预测方法能够提高矩阵的预测精度,能够在复杂的金融市场中构造低风险的资产组合。     

外汇市场微观结构理论浅析

文章详细介绍外汇市场微观结构理论的基本知识，介绍了这一领域的前沿课题及在国内进行研究面临的困难．并展望了该理论的前景。     

微观金融市场中逆向选择成本的估计模型

微观金融市场中的买入一卖出差价可以分割为定单处理成本、存货控制成本和逆向选择成本(信息不对称成本)三种成本因素，本文将重点分析其中的逆向选择成本估计模型。在对流行的五种估计逆向选择成本的模型分别进行描述之后，同时对这五种逆向选择成本的估计模型进行了简单的评论。     

中国证券市场的微观结构分析文献综述

市场微观结构理论也称市场微观结构经济学,是研究金融市场交易价格的形成、发现过程与交易运作机制的一个金融学分支.在传统的金融市场研究中,人们往往把金融资产价格作为一个宏观现象加以考察.但是从H.Demsetz于1968年发表了《交易成本》后,研究者对金融资产价格的考察角度转向金融市场运作的内在微观基础和金融资产买卖报价的价差关系.从微观角度来考察金融资产价格意味着可以将金融资产价格行为描述成经济主体最优化行为的结果.     

炸药微观结构对性能的影响研究

炸药属于一种危险物品,在我们日常的生产和生活中遇到的较少,炸药属于违禁品,在平时的管理中有严格的要求,一般情况下运用到军事、矿山的开采、隧道的挖掘等场所,炸药的性能对其使用有着重要的影响,在对炸药研究的过程中,炸药微观上的变化必然会引起宏观上的变化,必然会对炸药的性能产生影响,最终会影响炸药的爆炸性能。     

汇率决定的市场微观结构理论方法与发展前景

汇率决定市场微结构理论研究目的是揭示外汇市场微观结构因素或外汇市场交易层面因素对汇率短期运动的影响.近年来该领域理论成果相对集中于指令流与汇率决定的理论与实证方面的研究,文章就其进展进行分类回顾,对相关文献进行总体评价,最后对该领域的理论发展前景提出观点.     

异质金融市场驱动的已实现波动率计量模型

本文根据金融高频数据的典型特征和异质市场假说,首次提出了异质市场驱动因素的分层结构,并借此构建了已实现波动率的HAR-L-M计量模型。模拟分析显示出该模型的合理性和优越性,样本内、外预测都说明HAR-L-M模型优于现有已实现波动率HAR模型和ARFIMA模型。最后的实证分析结果显示,中国市场的异质程度要强于美国证券市场,同时个股更容易受多种异质驱动因素的影响,个股稳定性要比股指差。     

认购权证及标的股票波动率的实证分析

真实波动率是无法观测得到的，但已实现波动率是对真实波动率的一致性估计，由B—S公式计算而得的隐含波动率也是真实波动率的一个估计。文章着重介绍已实现波动率和隐含波动率的计算并在中国股票及权证市场进行实证分析，发现隐含波动率作为真实波动率的刻画具有很大的偏差，有力地说明我国权证市场上的高投机性。     

金融市场微观结构理论研究与我国二板市场交易结构的选择

一、金融市场微观结构理论的发展和最新成果 金融市场微观结构理论的思想源于古典价格理论,最早可以追溯到威廉·配第(WilliamPetty)和马歇尔(AMarshall)等人,但其正式诞生却是以1968年H·Demsetz发表的论文为标志的.Demsetz在该文中研究了证券市场上交易价格的形成与变化:从交易供给方的卖出报价和需求方的买入报价之间的差价形成过程出发,第一次提出了一个买卖报价价格差的模型.Demsetz认为,之所以买卖会出现报价差是因为买卖双方供求之间存在不平衡,买卖报价差其实是在有组织的市场中为交易的即刻性(immediacy)支付的加成.在此之后,金融市场微观结构理论开始逐渐被人们所认识,并随着时间的过去,其对于理解金融资产价格的形成从而完成市场交易结构、稳定市场,提高市场有效的重要性已经普遍被认同.到目前为止,金融市场微观结构理论的发展大致经历了两个阶段:     

程序化交易与市场微观结构的案例分析

2010年5月6日美股闪电暴跌,2007年8月6日开始的一周内美国多只对冲基金突然遭遇史无前例的亏损.文章基于案例分析的视角讨论程序化交易和算法交易对这两次事件的影响,然后从市场微观结构的角度分析程序化交易及其他算法交易对微观市场的变化,最后提出我国应对程序化交易的监管措施,以及如何有效地发展程序化交易.     

Improving variance forecasts: The role of Realized Variance features

In this paper, we effectively extend the Realized-EGARCH (R-EGARCH) framework by allowing the conditional variance process to incorporate exogenous variates related to different observable features of Realized Variance (RV). The choice of these features is well motivated by recent studies on the Heterogeneous Autoregressive (HAR) class of models. We examine several specifications nested within our augmented R-EGARCH representation, and we find that they perform significantly better than the standard R-EGARCH model. These specifications incorporate realized semi-variances, heterogeneous long-memory effects of RV, and jump variation. We also show that the performance of our framework further improves if we allow for skewness and excess kurtosis for asset return innovations, instead of assuming normality. This can better filter the true distribution of the return innovations, and thus can more accurately estimate their effects on the variance process. This is also supported by a Monte Carlo simulation exercise executed in the paper.     

BN周期成分的符号与我国GDP的真实周期

本文从理论上证明了以下的定理：当度量序列持久性的方差比大于1时,BN周期成分的符号应予反号,否则,不予反号。为验证定理,我们设计Monter-Carlo仿真实验,其结果也证实了理论定理。本文的理论结论和仿真结果,第一次从持久性的角度解释了文献中的“周期之谜”。在此基础上,我们应用BN周期分解方法和本文的理论结果,分解我国GDP的BN周期。结果显示,由于我国GDP的方差比为1.97,所以周期成分的符号应反号,由此形成我国GDP的真实周期。样本期内（2000Q2-2011Q4）我国共经历了六轮周期,这六轮周期不仅与我国实际经济增长的波动基本一致,而且与我国所遭遇的主要冲击相吻合;我国经济增长的周期具有波动幅度较大、持续时间又存在明显差异的特征。基于这些特征,本文认为,减弱我国经济增长的周期性波动,应成为宏观调控的重要内容。     

Predictive density estimators for daily volatility based on the use of realized measures

The main objective of this paper is to propose a feasible, model free estimator of the predictive density of integrated volatility. In this sense, we extend recent papers by Andersen et al. [Andersen, T.G., Bollerslev, T., Diebold, F.X., Labys, P., 2003. Modelling and forecasting realized volatility. Econometrica 71, 579–626], and by Andersen et al. [Andersen, T.G., Bollerslev, T., Meddahi, N., 2004. Analytic evaluation of volatility forecasts. International Economic Review 45, 1079–1110; Andersen, T.G., Bollerslev, T., Meddahi, N., 2005. Correcting the errors: Volatility forecast evaluation using high frequency data and realized volatilities. Econometrica 73, 279–296], who address the issue of pointwise prediction of volatility via ARMA models, based on the use of realized volatility. Our approach is to use a realized volatility measure to construct a non-parametric (kernel) estimator of the predictive density of daily volatility. We show that, by choosing an appropriate realized measure, one can achieve consistent estimation, even in the presence of jumps and microstructure noise in prices. More precisely, we establish that four well known realized measures, i.e. realized volatility, bipower variation, and two measures robust to microstructure noise, satisfy the conditions required for the uniform consistency of our estimator. Furthermore, we outline an alternative simulation based approach to predictive density construction. Finally, we carry out a simulation experiment in order to assess the accuracy of our estimators, and provide an empirical illustration that underscores the importance of using microstructure robust measures when using high frequency data.     

基于PVECM的综列协整检验临界值的计算

Groen和Kleibergen(2003)基于综列数据的误差纠正模型(PVECM)和极大似然估计方法,提出了与时间序列中Johanson(1991)协整检验类似的综列协整检验。其似然比检验统计量的极限分布是维纳过程的泛函,所以其临界值需要通过仿真试验来计算,但Groen和Kleibergen(2003)既没有给出具体的临界值也没有给出具体的程序。本文通过对维纳过程的随机积分进行仿真,估计基于PVECM的综列协整检验的临界值。与现有的部分临界值的比较结果显示,我们的计算程序是正确的,计算结果是可靠的。     

Estimation of ratio of population means in survey sampling when some observations are missing

This paper considers the estimation of the ratio of population means when some observations are missing. Four estimators are presented and their bias and mean square error properties are studied. Received: June 1998     

具有异质性非参数时间趋势的面板数据模型的估计

本文为一类具有异质性非参数时间趋势的面板数据模型提出了一种简单估计方法。基于局部多项式回归的思想,首先去除数据中的时间趋势成分,然后由最小二乘法来估计公共系数,同时得到时间趋势函数的非参数估计。在一些正则条件下,研究了这些估计量的渐近性质,即在时间维度T和横截面维度n同时趋向无穷时,建立了各个估计量的渐近相合性和渐近正态性。最后通过蒙特卡洛模拟,考查了这种估计方法的有限样本性质。     

变系数动态面板数据模型的半参数估计

本文把一般的常系数的动态面板数据模型拓广到变系数的情形。对于变系数的动态面板数据模型首先推导出模型所隐含的各种矩条件,然后利用广义矩估计的方法得到了模型中未知参数的半参数广义矩估计,最后对于我们所得到的估计的渐进性和一致性进行证明。     

Estimation of spot volatility with superposed noisy data

By using high frequency financial data, we nonparametrically estimate the spot volatility at any given time point, while the simultaneous presence of multiple transactions and market microstructure noise in the observation procedure are considered. Our estimator is based on the summation of the locally ranged increments, while kernel smoothing give us spot volatility. Besides, the microstructure noise can be estimated and removed, if it is modeled as bid-ask spread, which is a frequently used assumption. The consistency and asymptotic normality of the estimator are established. We do some simulation studies to assess the finite sample performance of our estimator. The estimator is also applied to some real data sets, further, the relationship between multiple records and spot volatility is also explored.     

Identification and Use of Efficient Faces and Facets in DEA

This paper provides an outline of possible uses of complete information on the facial structure of a polyhedral empirical production possibility set obtained by DEA. It is argued that an identification of all facets can be used for a characterization of basic properties of the empirical production frontier. Focus is on the use of this type of information for (i) the specification of constraints on the virtual multipliers in a cone-ratio model, (ii) a characterization of the data generation process for the underlying observed data set, and (iii) the estimation of isoquants and relevant elasticities of substitution reflecting the curvature of the frontier. The relationship between the so-called FDEF approach and the cone-ratio model is explored in some detail. It is demonstrated that a decomposition of the facet generation process followed by the use of one of the available (exponential) convex hull algorithms allows for an explicit identification of the facial structure of the possibility set in fairly large DEA data sets. It is a main point to be made that the difficulties encountered for an identification of all facets in a DEA-possibility set can be circumvented in a number of empirical data sets and that this type of information can be used for a characterization of the structural properties of the frontier.