Testing symmetry under a skew Laplace model

We develop tests of hypothesis about symmetry based on samples from possibly asymmetric Laplace distributions and present exact and limiting distribution of the test statistics. We postulate that the test statistic derived under the Laplace model is a rational choice as a measure of skewness and can be used in testing symmetry for other, quite general classes of skew distributions. Our results are applied to foreign exchange rates for 15 currencies.     

运用价格杠杆促进沈阳市水资源可持续利用

沈阳市是一个严重缺水的城市,保证水资源的效率分配对社会经济发展具有举足轻重的作用。水资源的合理需求难以自发形成,必须通过需求管理来实现,本文对沈阳市城市用水现状进行了分析,并进一步探讨了其经济原因,从而提出了利用价格杠杆调节城市用水供求的建议。     

新资本结构理论综述

随着资本结构研究的深入,理论界进一步放宽MM定理的基本假设。以Jensen,Myers,Ross,Leland,Harris,Hart等学者为代表的新资本结构理论引入最新的研究方法,对资本结构展开分析。本文按照新资本结构理论发展的历史轨迹,全面评述了资本结构理论中最为重要的各种理论,同时系统地描述了各有关理论的基本内容。     

基于EGARCH模型的我国股市信息对称性研究

利用过去17年我国上证综合指数的历史数据,根据股票市场大的波动周期分五阶段经过EGARCH(1,1)模型估计,以验证市场对信息冲出的反映情况.研究结果表明:中国股市存在很大的波动性,尚未达到弱有效性;存在正负杠杆效应交替出现的现象,表现出信息不对称性,但是这种不对称性在明显减小.     

可转换公司债券的杠杆效应研究

对于运用可转换公司债券进行理财的公司而言,充分了解可转换公司债券的杠杆效应是极其必要的。可转换公司债券在给发行公司带来财务杠杆效应的同时,也对发行公司的每股赢余产生稀释效应,但这一稀释效应要比股权融资对每股收益的影响低;可转换公司债券的价值与其股票的价值虽具有联动效应,但其间的关系较为复杂;可转换公司债券在为发行公司提供预防被收购的有利武器的同时,也为其持有者提供了间接购买股票的手段;可转换公司债券可缓解股东与债权人之间的代理问题、管理层和股东之间的利益冲突,有利于公司治理的结构完善。     

Generalized Leverage and its Applications

The generalized leverage of an estimator is defined in regression models as a measure of the importance of individual observations. We derive a simple but powerful result, developing an explicit expression for leverage in a general M -estimation problem, of which the maximum likelihood problems are special cases. A variety of applications are considered, most notably to the exponential family non-linear models. The relationship between leverage and local influence is also discussed. Numerical examples are given to illustrate our results     

基于《巴塞尔Ⅲ最终方案》的弹性杠杆率监管研究

弹性资本充足率监管加刚性杠杆率监管存在机理性缺陷。弹性资本充足率监管会影响刚性杠杆率监管的效果,刚性杠杆率监管也不能体现杠杆累积在时间维度和空间维度风险的变化。若引入弹性杠杆率缓冲,刚性杠杆率监管加弹性资本充足率监管的机理性缺陷就可以避免。因此,有必要实施弹性杠杆率监管,杠杆率的弹性化程度与银行的系统重要性程度相对应。     

BL-GARCH models with elliptical distributed innovations

In this work, we discuss the class of bilinear GARCH (BL-GARCH) models that are capable of capturing simultaneously two key properties of non-linear time series: volatility clustering and leverage effects. It has often been observed that the marginal distributions of such time series have heavy tails; thus we examine the BL-GARCH model in a general setting under some non-normal distributions. We investigate some probabilistic properties of this model and we conduct a Monte Carlo experiment to evaluate the small-sample performance of the maximum likelihood estimation (MLE) methodology for various models. Finally, within-sample estimation properties were studied using S&P 500 daily returns, when the features of interest manifest as volatility clustering and leverage effects. The main results suggest that the Student-t BL-GARCH seems highly appropriate to describe the S&P 500 daily returns.     

A high breakdown,high efficiency and bounded influence modified GM estimator based on support vector regression

Regression analysis aims to estimate the approximate relationship between the response variable and the explanatory variables. This can be done using classical methods such as ordinary least squares. Unfortunately, these methods are very sensitive to anomalous points, often called outliers, in the data set. The main contribution of this article is to propose a new version of the Generalized M-estimator that provides good resistance against vertical outliers and bad leverage points. The advantage of this method over the existing methods is that it does not minimize the weight of the good leverage points, and this increases the efficiency of this estimator. To achieve this goal, the fixed parameters support vector regression technique is used to identify and minimize the weight of outliers and bad leverage points. The effectiveness of the proposed estimator is investigated using real and simulated data sets.     

Allocation of resources in asymmetric competitions: How do the weak maintain a chance of winning?

To maintain a chance of occasionally beating a stronger player in a competition waged over several fields, a weaker player should give up on some of the fields and concentrate resources on the remaining ones. But when do weak players actually do this? And which fields do they give up when the fields differ in their likelihood of being assessed? We report an experimental study of resource allocation in which asymmetric pairs of players compete over asymmetric fields. Symmetric players and symmetric fields are used for control. We find that players behave as follows: (1) Average wins are the same in the symmetric and asymmetric fields conditions and correspond to relative player strength. (2) The proportion of fields given up on decreases with a player’s greater relative strength, increases for asymmetric field likelihoods, and increases when competitions are framed in meaningful context; this proportion is related to wins. (3) When field likelihoods are asymmetric, players’ resource allocation is correlated with likelihood. Wins generally increase with that correlation but the relation is different for players of different strength. (4) The proportion of fields given up on and the correlation with likelihood change with experience towards the values corresponding to higher wins.