Confidence interval of the jump activity index based on empirical likelihood using high frequency data

It is widely accepted that jumps exist in the asset price process. The jump activity index is a natural measure of how frequent the jumps are. Statistical inference of the jump activity index is of importance in determining the type of process that underlies the dynamics of the log price process. In this paper, we implement the empirical likelihood approach to construct the confidence interval of the jump activity index of a pure jump model using high frequency data. Wilks' theorem is established. We also extend the result on Zhao and Wu (2009)'s estimator to the more general framework in this paper. Simulation studies demonstrate the good performance of the empirical likelihood approach. Compared with the existing non-parametric estimator proposed by Zhao and Wu (2009), the empirical likelihood approach gives more accurate coverage probabilities in the simulation studies.     

Identification of quantitative trait loci for canine hip dysplasia by two sequential multipoint linkage analyses

Canine hip dysplasia (CHD) is characterized by hip laxity and subluxation that can lead to hip osteoarthritis. Studies have shown the involvement of multiple genetic regions in the expression of CHD. Although we have associated some variants in the region of fibrillin 2 with CHD in a subset of dogs, no major disease-associated gene has been identified. The focus of this study is to identify quantitative trait loci (QTL) associated with CHD. Two sequential multipoint linkage analyses based on a reversible jump Markov chain Monte Carlo approach were applied on a cross-breed pedigree of 366 dogs. Hip radiographic trait (Norberg Angle, NA) on both hips of each dog was tested for linkage to 21,455 single nucleotide polymorphisms across 39 chromosomes. Putative QTL for the NA was found on 11 chromosomes (1, 2, 3, 4, 7, 14, 19, 21, 32, 36, and 39). Identification of genes in the QTL region(s) can assist in identification of the aberrant genes and biochemical pathways involving hip dysplasia in both dogs and humans.     

价格跳跃行为视角下中国金融期货开盘效应的实证研究

基于JV‐T OD非参数方法和高频数据识别中国股指、国债期货日内价格跳跃行为,证明其开盘效应的存在,根据市场预期理论改进HAR‐CJ模型分析开盘效应的内在机制,主要结论有：（1）中国金融期货市场日内开盘效应明显,开盘跳跃行为是价格日内波动的重要组成部分;（2）股指期货日内价格的午盘和盘中跳跃行为是其显著区别于国债期货的日内分布特征;（3）期现市场开盘共同发生“常规性”跳跃时,期货市场开盘效应对现货市场的引导作用明显;（4）市场前期波动行为可以在一定程度上解释交易日内开盘效应,但相较而言,跳跃变差比连续波动的贡献稍弱。据此,提出为机构投资者和市场监管者提供相关风险管理、优化市场结构的建议。     

成就目标定向理论在蹲踞式跳远教学中的实验研究

通过文献资料法、实验法、数理统计法等对宿州学院体育学院2010级本科生两组男学生进行教学实验,通过整理数据并对比后发现:在进行蹲踞式跳远教学中,实验组学生在技术、成绩上都明显优于对照组的学生.说明成就目标定向理论优于传统教学方法.     

ISAR运动参数估计和补偿改进方法

在使用FFT距离多普勒算法进行ISAR成像处理时,回波相关性的减弱将加大运动补偿难度,带来较大的误差。该文在常规相邻相关法基础上,提出了一种改进的运动补偿方法。在距离向上,利用基准回波相关法与曲线拟合,克服了低回波相关性下包络对齐时出现的包络漂移、包络跳变等缺陷;在方位向上,利用DCFT变换,对目标的运动参数进行精确估计并加以补偿,减小了回波相关性降低对相位补偿的影响。仿真验证了该方法的有效性。     

BAYESIAN ESTIMATION OF RUIN PROBABILITIES WITH A HETEROGENEOUS AND HEAVY-TAILED INSURANCE CLAIM-SIZE DISTRIBUTION

This paper describes a Bayesian approach to make inference for risk reserve processes with an unknown claim‐size distribution. A flexible model based on mixtures of Erlang distributions is proposed to approximate the special features frequently observed in insurance claim sizes, such as long tails and heterogeneity. A Bayesian density estimation approach for the claim sizes is implemented using reversible jump Markov chain Monte Carlo methods. An advantage of the considered mixture model is that it belongs to the class of phase‐type distributions, and thus explicit evaluations of the ruin probabilities are possible. Furthermore, from a statistical point of view, the parametric structure of the mixtures of the Erlang distribution offers some advantages compared with the whole over‐parametrized family of phase‐type distributions. Given the observed claim arrivals and claim sizes, we show how to estimate the ruin probabilities, as a function of the initial capital, and predictive intervals that give a measure of the uncertainty in the estimations.     

十运会男子跳远运动员起跳阶段的参数分析

通过对十运会男子跳远运动员着地角、蹬地角、起跳扇面角的分析研究,认为改善此三项参数极为不合理的现状是实施训练过程的重要任务之一.继续提高运动员专项能力、更合理地安排整个训练过程,尽量避免过早的专项化训练带来的负面影响,加强膝关节快速用力条件下的退让式收缩能力和克制性收缩力量,是完成此任务的有效途径.     

女子跳远运动员起跳过程中摆动腿技术的研究

通过查阅有关文献资料,了解目前我国女子跳远助跑最后一步和起跳阶段有关参数的运动生物力学研究现状.主要对高水平女子跳远运动员的助跑最后一步和起跳过程中摆动腿的摆动作用及其相关因素进行分析与研究,找出我国女子跳远运动员在该技术上的差距及其原因,并对当今世界女子跳远摆动腿技术的发展趋势进行概括性的分析与总结.     

Bayesian dynamic models for survival data with a cure fraction

In this paper, we propose a new class of semi-parametric cure rate models. Specifically, we construct dynamic models for piecewise hazard functions over a finite partition of the time axis. Allowing the size of partition and the levels of baseline hazard to be random, our proposed models provide a great flexibility in controlling the degree of parametricity in the right tail of the survival distribution and the amount of correlations among the log-baseline hazard levels. Several properties of the proposed models are derived, and propriety of the implied posteriors with improper noninformative priors for regression coefficients based on the proposed models is established for the fixed partition of the time axis. In addition, an efficient reversible jump computational algorithm is developed for carrying out posterior computation. A real data set from a melanoma clinical trial is analyzed in detail to further demonstrate the proposed methodology.     

Bayesian model selection for D‐vine pair‐copula constructions

In recent years analyses of dependence structures using copulas have become more popular than the standard correlation analysis. Starting from Aas et al. ( 2009 ) regular vine pair‐copula constructions (PCCs) are considered the most flexible class of multivariate copulas. PCCs are involved objects but (conditional) independence present in data can simplify and reduce them significantly. In this paper the authors detect (conditional) independence in a particular vine PCC model based on bivariate t copulas by deriving and implementing a reversible jump Markov chain Monte Carlo algorithm. However, the methodology is general and can be extended to any regular vine PCC and to all known bivariate copula families. The proposed approach considers model selection and estimation problems for PCCs simultaneously. The effectiveness of the developed algorithm is shown in simulations and its usefulness is illustrated in two real data applications. The Canadian Journal of Statistics 39: 239–258; 2011 © 2011 Statistical Society of Canada