中、印、美股市联动差异性研究

基于扩散视角和跳跃视角探究了中、印、美股市联动行为。基于扩散视角,美国和印度股市与中国股市有明显的单向收益溢出效应,中美之间有明显的波动溢出效应,但是中印之间却不存在这种关系。从非对称影响的结果来看,只存在印度股市和美国股市与中国股市单向的非对称影响。基于跳跃视角,中印、中美股市的平均跳跃幅度和平均方差贡献率,与其跳跃强度相比联动性更高,中印联合跳跃比率相关系数和中美联合跳跃比率相关系数都处于较高水平,同时稳健性检验的结果表明结论整体具有一致性。     

我国企业IPO周期性波动中的制度因素

中国股市每一轮牛市的开始都是与经济发展相对应，和制度创新相结合，并与经济增长环境有密切的关系。从整体上来说，中国经济仍然处于高增长阶段，中国股市仍然是处于整体上升阶段。企业IPO状况与股市的发展戚戚相关，直接受经济政策的影响。     

中国股市波动性的统计分析

一、中国股市发展概况及存在的主要问题 (一)中国股市简要回顾 1990年12月19日上海证券交易所的正式开业,标志着我国证券集中性有形交易市场运作的开始.在十多年的短暂发展进程中,我国证券市场从无到有,从起步阶段的5只上市股票到1000多家公司在两个交易所挂牌交易,股票总发行股本达到了5997.93亿股,我国证券市场取得了辉煌的成就.     

如何发现有价值的高成长股

随着股市的迅速发展,参与股票投 资的人会越来越多,大到上市公司,专业投资机构,小到城镇家庭。但怎样投资最合理,如何选择最有投资价值的股票,是值得广大股民仔细研究的关键,本人涉入股市时间短,浅谈一些个人建议,仅供参考。一、高成长股与绩优股的比较与区别高成长股和绩优股是广大投资者的首选,但投资哪一种更赚钱？我们不妨从概念上和衡量的标准上做分析。绩优股顾名思义,业绩良好是重要条件,其评价标准有三个方面,一是每股每年税后利润在0.5元以上,二是年净资产收益率在20%以上,三是市盈率在20倍左右。另外还要根据企业…     

从统计实证分析破解中国M2/GDP畸高之迷

目前我国金融深化虽处于初期 ,但Ｍ2 ＧＤＰ比率却比发达国家为高 ,统计实证表明 ,此比率和通货比率的下滑、和货币流通速度的骤降以及金融资产的单一性有关 ,这背后折射出我国社会保障机制的缺陷 ,国有银行不良资产的负担沉重 ,以及金融资产多样性的匮乏 ,但不应夸大Ｍ2 ＧＤＰ比率和金融危机之间的相关性。　　一、谜语的提出 :畸高的Ｍ2 ＧＤＰ比率近年来 ,中国金融改革在悄然间形成了一个谜 :即广义货币 (Ｍ2 )与国内生产总值 (ＧＤＰ)的比值不断攀升。截止 2 0 0 0年 ,中国的Ｍ2 ＧＤＰ比值已达到 15 1% ,余永定教授称这一比重已是…     

影响新兴股市的多因素模型及与中国股市的比较

文章根据影响股票市场的微观和宏观因素，建立影响股票价格的多因素模型来分析１４个具有代表性的新兴股市的发展情况，并用逐步回归和主成份分析找出影响新兴股市的重要的、共同的因素。在此基础上，将我国股市的发展情况和新兴股市以及发达股市进行比较，找出存在的问题，以期为我国股市的发展提出建议。在这里新兴股市是指发展时间短，规模较小，大有潜力的发展中国家股市，中国股市属于新兴股市     

中国股票市场十年发展和波动的阶段性探析

股票市场是中国经济转轨过程中发展最快、影响最广、对社会触动最深的领域,文章从股票市场近十年的发展历程入手,分析中国股市价格波动的特征及波动原因,对股市发展和波动的历史分期进行划分。     

沪深股票市场相关性的实证研究

沪深股票市场相关性的实证研究韩德宗,徐剑刚中国大陆的股票市场是个年青的、发展和完善中的证券市场。过去三年多的时间,上海股市和深圳股市的股价变化是中国大陆股市发展的一个重要的侧面,它所留下的轨迹,值得我们去探索和总结。本文希望通过对上海股市以下简称沪市...     

中国股市和全球股市收益率联动性分析

随着全球化趋势不断加深,中国股市与全球股市联系日益紧密.自2004年1月到2010年6月,全球经济经历了稳定增长、急剧衰退、缓慢复苏三个过程,同样在股市中也得到反应.文章以代表中国股市的上证指数和代表全球股市的道琼斯指数为变量,采用VAR模型和脉冲响应函数进行实证分析,结果表明,在整个周期、急剧衰退阶段、缓慢复苏阶段全球股市对中国股市单方面格兰杰原因,但在稳定增长阶段,两者无明显影响.     

基于HMM的中国股市状态转换及预测

文章从偏度、峰度和移动方差三个角度对2000—2011年间的月度股票指数数据的波动性进行统计描述分析;运用隐藏马尔科夫模型,合理细分股市的五种股指状态,计算并结合中国股市的实际状况分析了股市在五种状态之间的变换规律。     

沪深A、B股市场信息传递路径实证分析

运用计量经济学中的ARCH-LM检验、GARCH模型、Granger引导关系检验等分析方法，实证分析了B股市场对境内投资者开放前后沪深两市A指收益率序列与B指收益率序列和非预期收益率序列的Granger引导关系，给出沪深A、B股市场信息传递路径，并且指出从信息流动角度来说，A、B股市场整合的方式是从A股市场向B股市场的内幕消息的传递和从B股市场向A股市场的投资理念的趋同。     

Detecting Randomness: A Review of Existing Tests with New Comparisons

In this article we review and compare a number of existing tests for detecting randomness in time series data, with emphasis on stock market index data. By comparing variance ratio tests with traditional statistical tests, we have the most extensive simulation comparison of such procedures. The investigated tests are compared over a diverse group of distributions, models, and stock market applications. In our stock market data analysis, the choice of data transformation can have a noticeable effect on test results. This study provides the reader with a guide as to which test and transformation is most appropriate for their use.     

On limiting likelihood ratio processes of some change-point type statistical models

Different change-point type models encountered in parametric statistical inference give rise to different limiting likelihood ratio processes. In this paper we consider two such likelihood ratios. The first one is an exponential functional of a two-sided Poisson process driven by some parameter, while the second one is an exponential functional of a two-sided Brownian motion. We establish that for sufficiently small values of the parameter, the Poisson type likelihood ratio can be approximated by the Brownian type one. As a consequence, several statistically interesting quantities (such as limiting variances of different estimators) related to the first likelihood ratio can also be approximated by those related to the second one. Finally, we discuss the asymptotics for large values of the parameter and illustrate the results by numerical simulations.     

Geometry of the log-likelihood ratio statistic in misspecified models

We show that the asymptotic mean of the log-likelihood ratio in a misspecified model is a differential geometric quantity that is related to the exponential curvature of Efron (1978), Amari (1982), and the preferred point geometry of [Critchley et al., 1993] and [Critchley et al., 1994]. The mean is invariant with respect to reparameterization, which leads to the differential geometrical approach where coordinate-system invariant quantities like statistical curvatures play an important role. When models are misspecified, the likelihood ratios do not have the chi-squared asymptotic limit, and the asymptotic mean of the likelihood ratio depends on two geometric factors, the departure of models from exponential families (i.e. the exponential curvature) and the departure of embedding spaces from being totally flat in the sense of Critchley et al. (1994). As a special case, the mean becomes the mean of the usual chi-squared limit (i.e. the half of the degrees of freedom) when these two curvatures vanish. The effect of curvatures is shown in the non-nested hypothesis testing approach of Vuong (1989), and we correct the numerator of the test statistic with an estimated asymptotic mean of the log-likelihood ratio to improve the asymptotic approximation to the sampling distribution of the test statistic.     

股市危机中股指期货应该限制交易吗——基于2015年股市危机的实证分析

利用上证50、沪深300和中证500股指期货合约及其相应指数的高频数据,克服了传统BEKK和DCC模型的不足,通过建立VECM-DCC-VARMA-AGARCH模型考察股市危机期间中国股指期货市场与股票市场之间的信息传导关系与风险传染效应。研究结果表明,股市危机期间股指期货具有很强的价格引导和风险传染效应,股指期货的持续波动加剧了股票市场的进一步波动。因此,提出风险传染效应与市值规模相关、非对称效应和非预期冲击效应与市值规模负相关、波动的风险传染效应与市值规模正相关。危机时期,应抑制股指期货市场上的过度投机,对股指期货采取限制开仓、提高交易保证金和交易手续费都是正确和切实可行的措施。建议监管当局健全股指期货和股票市场交易制度。     

Chain ratio type estimator for ratio of two population m3ans using auxiliary characters

In this paper we have proposed chain ratio type estimators for ratio of two population means using two auxiliary characters. The expressions for bias and mean square error of these estimators have been derived. A comparison of the proposed estimator with that of double sampling estimator has been made in terms of mean square error. An emperical study has also been made.     

Optimal detection of a jump in the intensity of a Poisson process or in a density with likelihood ratio statistics

We consider the problem of detecting a ‘bump’ in the intensity of a Poisson process or in a density. We analyze two types of likelihood ratio‐based statistics, which allow for exact finite sample inference and asymptotically optimal detection: The maximum of the penalized square root of log likelihood ratios (‘penalized scan’) evaluated over a certain sparse set of intervals and a certain average of log likelihood ratios (‘condensed average likelihood ratio’). We show that penalizing the square root of the log likelihood ratio — rather than the log likelihood ratio itself — leads to a simple penalty term that yields optimal power. The thus derived penalty may prove useful for other problems that involve a Brownian bridge in the limit. The second key tool is an approximating set of intervals that is rich enough to allow for optimal detection, but which is also sparse enough to allow justifying the validity of the penalization scheme simply via the union bound. This results in a considerable simplification in the theoretical treatment compared with the usual approach for this type of penalization technique, which requires establishing an exponential inequality for the variation of the test statistic. Another advantage of using the sparse approximating set is that it allows fast computation in nearly linear time. We present a simulation study that illustrates the superior performance of the penalized scan and of the condensed average likelihood ratio compared with the standard scan statistic.     

A self-adjusted weighted likelihood ratio test for global clustering of disease

Compared to tests for localized clusters, the tests for global clustering only collect evidence for clustering throughout the study region without evaluating the statistical significance of the individual clusters. The weighted likelihood ratio (WLR) test based on the weighted sum of likelihood ratios represents an important class of tests for global clustering. Song and Kulldorff (Likelihood based tests for spatial randomness. Stat Med. 2006;25(5):825–839) developed a wide variety of weight functions with the WLR test for global clustering. However, these weight functions are often defined based on the cell population size or the geographic information such as area size and distance between cells. They do not make use of the information from the observed count, although the likelihood ratio of a potential cluster depends on both the observed count and its population size. In this paper, we develop a self-adjusted weight function to directly allocate weights onto the likelihood ratios according to their values. The power of the test was evaluated and compared with existing methods based on a benchmark data set. The comparison results favour the suggested test especially under global chain clustering models.     

Confidence intervals for the ratio of two variances

In this paper we consider confidence intervals for the ratio of two population variances. We propose a confidence interval for the ratio of two variances based on the t-statistic by deriving its Edgeworth expansion and considering Hall's and Johnson's transformations. Then, we consider the coverage accuracy of suggested intervals and intervals based on the F-statistic for some distributions.