Estimation of the marginal expected shortfall under asymptotic independence

We study the asymptotic behavior of the marginal expected shortfall when the two random variables are asymptotic independent but positively associated, which is modeled by the so-called tail dependent coefficient. We construct an estimator of the marginal expected shortfall, which is shown to be asymptotically normal. The finite sample performance of the estimator is investigated in a small simulation study. The method is also applied to estimate the expected amount of rainfall at a weather station given that there is a once every 100 years rainfall at another weather station nearby.     

Beyond tail median and conditional tail expectation: Extreme risk estimation using tail Lp-optimization

The conditional tail expectation (CTE) is an indicator of tail behavior that takes into account both the frequency and magnitude of a tail event. However, the asymptotic normality of its empirical estimator requires that the underlying distribution possess a finite variance; this can be a strong restriction in actuarial and financial applications. A valuable alternative is the median shortfall (MS), although it only gives information about the frequency of a tail event. We construct a class of tail L^p-medians encompassing the MS and CTE. For p in (1,2), a tail L^p-median depends on both the frequency and magnitude of tail events, and its empirical estimator is, within the range of the data, asymptotically normal under a condition weaker than a finite variance. We extrapolate this estimator and another technique to extreme levels using the heavy-tailed framework. The estimators are showcased on a simulation study and on real fire insurance data.     

Kurtosis modelling by means of the J-transformation

Summary: The H–family of distributions or H–distributions, introduced by Tukey (1960; 1977), are generated by a single transformation of the standard normal distribution and allow for leptokurtosis represented by the parameter h. Alternatively, Haynes et al. (1997) generated leptokurtic distributions by applying the K–transformation to the normal distribution. In this study we propose a third transformation, the so–called J–transformation, and derive some properties of this transformation. Moreover, so-called elongation generating functions (EGFs) are introduced. By means of EGFs we are able to visualize the strength of tail elongation and to construct new transformations. Finally, we compare the three transformations towards their goodness–of–fit in the context of financial return data.     

Diagnostics for dependence within time series extremes

Summary. The analysis of extreme values within a stationary time series entails various assumptions concerning its long- and short-range dependence. We present a range of new diagnostic tools for assessing whether these assumptions are appropriate and for identifying structure within extreme events. These tools are based on tail characteristics of joint survivor functions but can be implemented by using existing estimation methods for extremes of univariate independent and identically distributed variables. Our diagnostic aids are illustrated through theoretical examples, simulation studies and by application to rainfall and exchange rate data. On the basis of these diagnostics we can explain characteristics that are found in the observed extreme events of these series and also gain insight into the properties of events that are more extreme than those observed.     

紧贴行业的应用型人才培养模式之研究

广东白云学院在推进汽车检测与维修技术专业教学改革过程中,紧紧围绕汽车服务业的现状和特点,以行业人才需求为依据,确定专业培养目标和人才规格,以行业的岗位能力要求为出发点,构建高效、实用的培养方案,以服务于行业为目标,建立有行业参与的教学机制,在人才培养质量上取得了优异的成绩。     

汽车工业的国际化战略发展模式探析

面对中国汽车工业技术落后 ,零部件技术开发能力弱 ,科研和产品开发资金投入不足的现状 ,我国的汽车工业要想与技术先进、资金实力雄厚的大型汽车厂商一争雌雄 ,就必须走一条有中国特色的汽车工业国际化的发展道路     

Analytical approximations for iterated bootstrap confidence intervals

Standard algorithms for the construction of iterated bootstrap confidence intervals are computationally very demanding, requiring nested levels of bootstrap resampling. We propose an alternative approach to constructing double bootstrap confidence intervals that involves replacing the inner level of resampling by an analytical approximation. This approximation is based on saddlepoint methods and a tail probability approximation of DiCiccio and Martin (1991). Our technique significantly reduces the computational expense of iterated bootstrap calculations. A formal algorithm for the construction of our approximate iterated bootstrap confidence intervals is presented, and some crucial practical issues arising in its implementation are discussed. Our procedure is illustrated in the case of constructing confidence intervals for ratios of means using both real and simulated data. We repeat an experiment of Schenker (1985) involving the construction of bootstrap confidence intervals for a variance and demonstrate that our technique makes feasible the construction of accurate bootstrap confidence intervals in that context. Finally, we investigate the use of our technique in a more complex setting, that of constructing confidence intervals for a correlation coefficient.     

新能源汽车产业商业模式创新多要素联动机制研究 ———基于创新生态系统视角

基于创新生态系统理论和种群关系理论,将我国新能源汽车产业上市公司划分为不同生态位 企业种群。 运用模糊集定性比较分析法,从资源基础、企业家精神、技术创新、激励水平和环境动态性 5 个维度出发,探究不同生态位新能源汽车企业种群商业模式创新的联动机制。 研究结果表明:低生态位 企业种群存在“技术创新-激励水平”“技术创新-环境动态性”两种高水平商业模式创新联动机制;中生 态位企业种群主要通过内部资源基础和企业家精神驱动来实现商业模式创新发展;高生态位企业种群存 在“企业家精神-环境动态性”“企业家精神”“激励水平-环境动态性”三种商业模式要素联动机制。     

重庆汽车产业全产业链发展的现状与思考

重庆作为中国汽车产业都城之一,经过多年发展,汽车产业全产业链不断完善,品牌竞争力不断增强,但同时也出现了诸如产业链不紧密、创新能力不强等现实问题,这为研究重庆汽车产业全产业链提出了迫切要求。文章通过实证分析方法,分析重庆汽车产业全产业链发展现状,从理论与实践角度提出进一步完善重庆汽车产业全产业链的建议。     

Semi-polynomial copulas

In this paper, we characterise a family of bivariate copulas whose sections between the main diagonal and the border of the unit square are polynomial, generalising several families of copulas, including those with quadratic and cubic sections. We also study a measure of association and the tail dependence for this class, illustrating our results with several examples.