时间序列多个突变点的贝叶斯推断——对我国GDP序列的实证分析

突变点的存在对经济分析与建模会产生重要影响."邹检验"仅仅在序列存在一个突变点时有效.为了对序列中可能存在的多个突变点进行判断,引入了基于贝叶斯推断的多个突变点判断理论,并将该理论应用于我国GDP序列中.笔者检测出该序列存在三个突变点,分别位于1961年,1976年,1989年.此外,发现加入合理的突变点后,模型的预测精度得到显著的提高.     

基于具有LR型模糊输出回归模型的保费预测

在保费预测研究中,提出了一种基于模糊回归模型的预测方法.采用模糊最小二乘法,针对清晰输入和LR型模糊输出,在考虑输出量隶属函数类型存在差异问题基础之上,得到模型回归系数的迭代解.通过最小二乘估计的定性分析,给出检验模型拟合度的指标.结合保费数据的预测结果表明模型可行且具有较强的解释能力.     

基于GM(1,1)模型的新疆保险业“十二五”发展预测

选择新疆2002—2010年的保费收入,保险密度,保险深度这三项指标,其中将保费收入划分为财产险保费收入和人身险保费收入,对新疆保险业"十二五"发展进行预测.采用的预测方法是灰色系统理论中的GM(1,1)预测模型(一阶一元灰色模型).并对预测结果进行定性分析,提炼出本文的结论,为新疆保险业"十二五"发展战略提供坚实的数据支撑.     

相依风险模型下风险保费的信度估计

建立了风险之间呈现某种特殊相依结构的信度模型.利用正交投影的方法,得到了相依风险模型下的Bühlmann信度保费和Bühlmann-Straub信度保费,并讨论了信度估计的统计性质.结论表明,在风险之间呈现相依结构时,信度预测是个体索赔均值,总索赔均值和聚合保费三者的加权和,从而推广了经典的信度理论.     

GAMLSS模型在车险定价中的应用

在系统梳理国内外非寿险产品费率厘定方法的基础上,详细介绍了GAMLSS模型,证明了在位置参数和尺度参数的预测中均引入随机效应的GAMLSS模型可更有效地解释纵向数据中个体间的异质性.最后将GAMLSS模型应用于一组纵向车辆保险数据,计算了先验保费、后验保费、后验风险保费和奖惩因子.实证结果表明,GAMLSS模型不仅可为非寿险产品的定价提供依据,而且使风险分类更加稳定、合理.     

广义线性模型在汽车延保风险保费测算中的应用

基于保险公司2010年1月—2019年3月的实际保单数据样本,分别运用广义线性模型中的泊松模型和伽玛模型测算出险频率和案均赔款,构建风险保费测算模型,对影响风险保费的因素进行定量研究及分析.结果表明:该方法能够构建多个变量与风险保费的数值关系,减少了信息的损失,得到的费率表可作为实际应用的参考.最后,通过该方法测算结果与市场定价的实例比较对方法的合理性与优越性进行了说明.     

广义线性模型在汽车延保风险保费测算中的应用（英文）

基于保险公司2010年1月—2019年3月的实际保单数据样本,分别运用广义线性模型中的泊松模型和伽玛模型测算出险频率和案均赔款,构建风险保费测算模型,对影响风险保费的因素进行定量研究及分析.结果表明:该方法能够构建多个变量与风险保费的数值关系,减少了信息的损失,得到的费率表可作为实际应用的参考.最后,通过该方法测算结果与市场定价的实例比较对方法的合理性与优越性进行了说明.     

保费再投资下带干扰的COX风险模型的破产概率

基于经典的风险模型,考虑了对于保费进行稳健投资的情况,同时加入了用布朗运动来描述的干扰因素,引入了保费再投资下带干扰的Cox风险模型.利用鞅方法得到了该模型破产概率的Lundberg不等式.     

改进后的复合Poisson-Geometric风险模型Gerber-Shiu折现惩罚函数

在考虑到因保费收入和通货膨胀等随机干扰的影响,以及将多余资本用于投资来提高赔付能力的基础上,文章对复合Poisson-Geometric风险模型做进一步推广,建立以保费收入服从复合Poisson过程,理赔量服从复合Poisson-Geometric过程的带投资的干扰风险模型,针对该风险模型,应用全期望公式,推导了Gerber-Shiu折现惩罚函数满足的更新方程,进而得到了在破产时盈余惩罚期望,破产赤字和破产概率满足的更新方程.并以保费额和索赔额均服从指数分布为例,给出破产概率满足的微分方程.以及通过数值例子,分析了初始准备金额,投资金额及保费额等对保险公司最终破产概率的影响.结论为经营者或决策者对各种金融或保险风险进行定量分析和预测提供了理论依据.     

期望效用原理中风险保费的信度估计

期望效用保费定价方法是保费定价的重要方法之一.本文建立了期望效用保费原理的贝叶斯模型,定义了期望效用原理的风险保费,并给出了风险保费的信度估计.进而,研究了保费估计的统计性质.最后通过数值模拟的方法验证了风险保费估计的渐近正态性和收敛速度.     

极值理论及其在巨灾再保险定价中的应用

巨灾损失中往往存在极端值,一般统计分布对其拟合效果欠佳,本文运用极值理论对极端值建模,基于分层定价的思想,在不同的起赔点下对再保险超额损失部分的定价进行了探讨,并以洪水损失数据为例进行了实证研究,拟合了POT模型,得到了洪水再保险纯保费。     

Spline Estimation of Discontinuous Regression Functions

Abstract

This article deals with regression function estimation when the regression function is smooth at all but a finite number of points. An important question is: How can one produce discontinuous output without knowledge of the location of discontinuity points? Unlike most commonly used smoothers that tend to blur discontinuity in the data, we need to find a smoother that can detect such discontinuity. In this article, linear splines are used to estimate discontinuous regression functions. A procedure of knot-merging is introduced for the estimation of regression functions near discontinuous points. The basic idea is to use multiple knots for spline estimates. We use an automatic procedure involving the least squares method, stepwise knot addition, stepwise basis deletion, knot-merging, and the Bayes information criterion to select the final model. The proposed method can produce discontinuous outputs. Numerical examples using both simulated and real data are given to illustrate the performance of the proposed method.     

投资者注意的风险补偿对股市回报的预测

利用历史累积交易金额数据,本文构造了中国股票市场增量注意风险补偿和存量注意风险补偿,并检验其对中国股票市场收益率的预测能力。样本外检验结果显示,以上两种注意风险补偿均能显著预测下个月中国股市的超额收益率,其R²分别达到了2.68%和2.50%;与中国股票市场中其他预测变量相对比,增量注意和存量注意风险补偿表现出更强的预测能力。此外,基于不同的样本外检验期、不同的风险厌恶参数以及五种不同的变量构造方式,投资者注意风险补偿均产生显著的预测能力。围绕着经济周期波动,本文对注意风险补偿的预测能力进行了解释,同时还发现,相较于经济衰退期间,经济繁荣期间的投资者注意风险补偿样本外预测能力更强。     

Stability of discontinuity structures described by a generalized KdV–Burgers equation

The stability of discontinuities representing solutions of a model generalized KdV–Burgers equation with a nonmonotone potential of the form φ(u) = u⁴–u² is analyzed. Among these solutions, there are ones corresponding to special discontinuities. A discontinuity is called special if its structure represents a heteroclinic phase curve joining two saddle-type special points (of which one is the state ahead of the discontinuity and the other is the state behind the discontinuity).The spectral (linear) stability of the structure of special discontinuities was previously studied. It was shown that only a special discontinuity with a monotone structure is stable, whereas special discontinuities with a nonmonotone structure are unstable. In this paper, the spectral stability of nonspecial discontinuities is investigated. The structure of a nonspecial discontinuity represents a phase curve joining two special points: a saddle (the state ahead of the discontinuity) and a focus or node (the state behind the discontinuity). The set of nonspecial discontinuities is examined depending on the dispersion and dissipation parameters. A set of stable nonspecial discontinuities is found.     

Detecting discontinuity points from spectral data with the quotient-difference (qd) algorithm

This paper introduces a new technique for the localization of discontinuity points from spectral data. Through this work, we will be able to detect discontinuity points of a 2π-periodic piecewise smooth function from its Fourier coefficients. This could be useful in detecting edges and reducing the effects of the Gibbs phenomenon which appears near discontinuities and affects signal restitution. Our approach consists in moving from a discontinuity point detection problem to a pole detection problem, then adapting the quotient-difference (qd) algorithm in order to detect those discontinuity points.     

电力负荷预测的遗传神经网络模型研究

根据电力负荷预测的特点,提出遗传神经网络负荷预测模型,有效地克服了人工神经网络学习速度慢、存在局部极小点的固有缺陷,经实例验证,该方法能有效地提高预测精度和速度。     

过度自信与风险溢价研究

非理性投资者的心理会影响风险溢价。本文基于投资者的过度自信心理偏差构建了证券投资的理性风险溢价度量模型、非理性风险溢价度量模型,并利用理性投资者和非理性投资者的相互作用,构建了证券投资的市场风险溢价度量模型,研究了非理性风险溢价对理性风险溢价和市场风险溢价的偏离问题。研究结论表明:非理性风险溢价偏离市场风险溢价的程度依赖于非理性投资者的市场价值权重。     

A novel two-factor forecasting model for fuzzy time series

The study of fuzzy time series has increasingly attracted much attention due to its salient capabilities of tackling vague and incomplete data. A variety of forecasting models have devoted to improving forecasting accuracy, however, the issue of partitioning intervals has rarely been investigated. Recently, we proposed a novel deterministic forecasting model to eliminate the major overhead of determining the k-order issue in high-order models. This paper presents a continued work with focusing on handling the interval partitioning issue by applying the fuzzy c-means technology, which can take the distribution of data points into account and produce unequal-sized intervals. In addition, the forecasting model is extended to allow process twofactor problems. The accuracy superiority of the proposed model is demonstrated by conducting two empirical experiments and comparison to other existing models. The reliability of the forecasting model is further justified by using a Monte Carlo simulation and box plots. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

一类有界函数的可积问题探讨

讨论闭区间上有无穷多个不连续点的有界函数的可积问题,所得结果是"闭区间上不连续的点仅有有限个的函数可积"的推广.     

On the structure of generalized solutions of the one-dimensional equations of a polytropic viscous gas

A model system of equations that defines the unsteady one-dimensional flow of a visoucs gas is considered on the assumption that the pressure is determined by the adiabatic Poisson law. Generalized solutions are investigated in the class of discontinuous functions, a class of correctness is separated, and the structure of solutions of this class is clarified. It is shown that the initial velocity discontinuities are instantly smoothed out, and from the discontinuity points of the initial density,lines of contact discontinuity are formed. These lines exist for an infinite time, and the pressure jumps on them vanish exponentially.