太阳辐射时间序列的非线性检验

检验太阳辐射时间序列是否有非线性特征,对于分析、建模和预测太阳辐射量是重要、有益的.提出用基于替代数据的检验方法来检验太阳辐射时间序列是否存在非线性特征,并将数据序列的三阶矩作为检验统计量.选取了美国Montana州Dillon地区和Wyoming州Green Rivet地区每日总辐射量、Utah州Moab地区的每月日平均总辐射量时间序列作为检验对象.数值分析的统计结果表明所研究的日总辐射时间序列存在非线性,而每月日平均总辐射时间序列未检测出非线性.因而,对太阳辐射时间序列建模和预测之前,检验其是否有非线性特征是必要的.     

具有结构变化的非线性回归模型的阶段异方差检验

对于具有结构变化的非线性回归模型,两阶段的随机误差同时具有方差齐性是一个基本假设,但是该假设未必正确．本文研究该模型阶段异方差的检验问题．首先探讨了两阶段异方差的同时检验,然后构造了两阶段异方差的两个单个检验,分别得到了同时检验和单个检验的score统计量以及相应的调整形式．然后应用得到的检验统计量分析了南澳大利亚洋葱数据的阶段异方差性(Ratkowsky,1983),并用AIC,SBC进行模型比较,得到的结果与检验结果非常吻合．最后,用Monte Carlo模拟方法研究了统计量的检验功效．     

基于连续可分的广义非线性纵向数据模型偏离名义离差的score检验及其功效

指数族非线性模型或广义非线性模型是广义线性模型和正态回归模型的自然推广.本文针对可分的连续型指数族回归模型(如正态模型,Γ模型,逆高斯模型),讨论广义非线性纵向数据模型中偏离名义离差的检验问题,得到了检验的score统计量,并推导了它们的渐近分布和局部近似功效.然后利用Monte Carlo方法研究了检验统计量的性质.最后利用百慕大草地数据说明了检验方法的应用.     

长期事件研究方法论——一个综述

本文对国外长期事件研究方法论文献进行了全面的梳理,并着重介绍和分析了期望收益模型(或收益基准)选择、异常收益度量,以及检验统计量的设定与检验力等。研究发现,在各期望收益模型、两种度量异常收益方法—AAR(或CAR)与BHAR的选择,以及各检验统计量是否存在错误设定等问题上,国外学界并未达成共识,争论仍在继续。     

考虑方差结构突变的股市收益波动非对称性研究

股市收益波动非对称性的研究对于构建准确的资产价格模型以及市场波动性的预测来说都是至关重要的.但在我国股市收益波动中是否存在内生的结构突变,结构突变是否对股市收益波动的非对称性特征产生影响等问题上却缺乏探讨.利用引入了结构突变的ARCH族模型考察了我国股市收益波动的非对称性.研究结果发现,引入结构突变后的ARCH族模型对股市收益波动的拟合效果更好.在考虑了结构突变后,股市收益波动的持续性降低,非对称性现象虽然存在,但好消息和坏消息对股市收益波动的影响程度却发生了变化.     

基于Beta分布形状的拟合优度检验

本文指出了拟合优度检验中选用经验频率公式时存在的误区,对顺序统计量失效概率分布进行了偏态和峰态分析,提出了一个基于Beta分布形状特征的经验分布函数,给出了精确值和近似值两种计算方法,在此基础上建立新的极值型检验统计量．利用Monte Carlo方法进行数值模拟,得到0．01、0．05、0．1显著度水平下检验统计量的临界值,并利用常用的分布模型进行检验功效比较,数值模拟结果表明基于分布形状的经验频率公式能更好地反映顺序统计量失效概率分布的集中趋势,证明了本文提出的两种检验统计量在中小样本条件下具有更优的检验功效．     

具有ARIMA（0，1，0）对称误差的非线性模型的统计诊断

本文讨论具有ARIMA(0,1,0)对称误差的非线性模型的异方差检验和局部影响分析.对称误差分布族包括正态,t,power exponential,logistics Ⅰ,Ⅱ,污染正态等所有对称连续分布.文章首先导出了关于白噪声异方差检验的score统计量及其调整形式,然后对模型进行了局部影响分析,得到了基于似然函数扰动和反应变量扰动的诊断统计量.最后,利用实际数据说明了检验方法的应用,并用Monte Carlo模拟方法研究了异方差检验统计量的检验功效.     

具有随机删失数据的部分线性模型的拟合优度检验的渐近性质

研究随机删失部分线性回归模型的假设检验问题. 提出了一个检验统计量来检验数据是否满足一个部分线性回归模型, 它是基于残差的cusum过程的平方形式. 研究了零假设下和局部对立假设下检验统计量的渐近分布. 数值模拟表明该检验方法有好的检验功效.     

半参数可加测量误差模型的白噪声检验

当模型误差不是白噪声时,通常的估计方法无效,特别是当回归因子包含后延变量时,估计不相合.因此,文章研究了半参数可加测量误差模型的白噪声检验.提出了一个白噪声检验统计量,并在模型误差是白噪声的零假设下证明了所提检验统计量服从渐近正态分布.随机模拟表明所提出的检验统计量具有良好的检验功效和水平.     

变结构面板协整检验的响应面函数研究

Panel-ρ检验是常用的异质面板数据协整检验统方法,本文通过Monte Carlo模拟分析Panel-ρ协整检验方法的小样本性质,以及该方法对于变结构面板协整检验的检验功效.结果表明,在小样本情况下Panel-ρ统计量在原假设下的渐进分布会不同于该统计量的理论渐进分布,而且面板数据中存在的结构变化也会对渐进分布产生影响,从而降低Panel-ρ检验的检验功效.为了得到更加符合实际样本情况的统计量临界值,通过Monte Carlo模拟方法得到Panel-ρ协整检验方法的响应面函数,建立了统计量的临界值与面板数据的样本容量、结构变化类型的直接函数关系.Monte Carlo模拟检验表明,响应面函数法确实能够改善Panel-ρ协整检验的检验功效,在小样本容量和具有结构变化的情况下保证了面板协整检验的有效性.     

双阀值LSTAR模型及其非线性检验

本文首先简要介绍了平滑转换回归模型(STR)的含义和检验其非线性的程序,然后以汇率均值回复问题为例说明目前流行的单阀值STR模型有其局限性,存在研究双阀值STR模型的必要。为此,本文对双阀值LSTAR模型的非线性检验进行了分析。结果表明,不同于单阀值STAR模型需要对转换函数进行三阶Taylor展开,双阀值LSTAR模型只需对转换函数进行一阶展开即可,因此大大节省了自由度。     

线性模型中自相关的经验似然比检验

研究线性回归模型中的自相关检验问题,用经验似然的方法构造检验统计量,得到了零假设下检验统计量的渐近分布,我们的检验方法不但可以检验一阶自相关,也可以检验高阶自相关,数值模拟表明检验方法具有良好的检验功效.     

部分线性模型序列相关的经验似然比检验

本文研究了部分线性回归模型中误差的序列相关性的检验问题,用经验似然的方法构造检验统计量,得到了零假设下检验统计量的渐近分布,我们的检验方法不但可以检验一阶序列相关,也可以检验高阶序列相关,数值模拟表明检验方法有好的检验功效．     

中国外汇市场压力指数与货币政策关联性——基于TVP-VAR方法的实证分析

为了正确评估中国外汇市场运行状况,本文首次选取有效汇率、外汇储备、中外利差和汇率预期,并首次使用GIRF方法构建中国EMPI。本文考虑经济数据发生结构突变的可能性,引入TVP-VAR方法研究EMPI与货币政策关联性,实证结果表明:2005年7月至2011年1月,人民币升值压力的月份居多;2011年2月至2015年12月,人民币贬值压力的月份居多;经济增长、国内信贷均与EMPI有相互引导的关系,且在不同时期会有所差异。此外,TVP-VAR方法的实证结果通过了稳健性检验。     

A comparison of bootstrap and Monte-Carlo testing approaches to value-at-risk diagnosis

In this note we investigate a particular resampling scheme and Monte Carlo testing to determine critical values for two test statistics typically used for diagnosing value-at-risk models. In cases of small nominal coverage subjected to testing, the dynamic quantile test and a corresponding logit based likelihood ratio test suffer from poor convergence to the asymptotic limit distribution. In terms of empirical size both resampling and Monte Carlo approaches offer most accurate test features with the Monte Carlo technique achieving power gains if a misspecified value-at-risk model is subjected to testing.     

Model checking for a general linear model with nonignorable missing covariates

In this paper, we investigate the model checking problem for a general linear model with nonignorable missing covariates. We show that, without any parametric model assumption for the response probability, the least squares method yields consistent estimators for the linear model even if only the complete data are applied. This makes it feasible to propose two testing procedures for the corresponding model checking problem: a score type lack-of-fit test and a test based on the empirical process. The asymptotic properties of the test statistics are investigated. Both tests are shown to have asymptotic power 1 for local alternatives converging to the null at the rate n-r, 0 ≤ r < 1/2 . Simulation results show that both tests perform satisfactorily.     

Market efficiency of Brazilian exchange rate: Evidence from variance ratio statistics and technical trading rules

This study utilizes the variance ratio test to examine the behavior of Brazilian exchange rate. We show that adjustments for multiple tests and a bootstrap methodology must be employed in order to avoid size distortions. We propose a block bootstrap scheme and show that it has much nicer properties than the traditional Chow–Denning [Chow, K.V., Denning, K.C., 1993. A simple multiple variance ratio test. Journal of Econometrics 58 (3), 385–401] multiple variance ratio tests. Overall, the method proposed in the paper provides evidence refuting the random walk behavior for the Brazilian exchange rate for long investment horizon, but consistent with the random walk hypothesis for short-run horizon. Additionally, we also test for the predictive power of variable moving average (VMA) and trading range break (TRB) technical rules and find evidence of forecasting ability for these rules. Nonetheless, the excess return that can be obtained from such rules is not significant, suggesting that such predictability is not economically significant.     

Nonlinearity tests for bilinear systems

The purpose of this paper is to develop nonlinearity tests for open-loop bilinear systems. Lagrange multiplier tests of linear systems against a bilinear alternative are proposed. A simulation study is performed to check the validity of the asymptotic null distributions of the test statistics and to investigate the power characteristics of the tests. Two recent nonlinearity tests in the time-series context are adapted to linear systems and compared with Lagrange multiplier tests. Simulation results show that the proposed Lagrange multiplier tests are more powerful than the other tests.     

Necessary and sufficient conditions for power convergence rate of approximations in Tikhonov’s scheme for solving ill-posed optimization problems

We investigate a rate of convergence of estimates for approximations generated by Tikhonov’s scheme for solving ill-posed optimization problems with smooth functionals under a structural nonlinearity condition in a Hilbert space, in the cases of exact and noisy input data. In the noise-free case, we prove that the power source representation of the desired solution is close to a necessary and sufficient condition for the power convergence estimate having the same exponent with respect to the regularization parameter. In the presence of a noise, we give a parameter choice rule that leads for Tikhonov’s scheme to a power accuracy estimate with respect to the noise level.     

Nonexistence of global solutions for generalized Tricomi equations with combined nonlinearity

In the present paper, we investigate the blow-up dynamics for local solutions to the semilinear generalized Tricomi equation with combined nonlinearity. As a result, we enlarge the blow-up region in comparison to the ones for the corresponding semilinear models with either power nonlinearity or nonlinearity of derivative type. Our approach is based on an iteration argument to establish lower bound estimates for the space average of local solutions. Finally, we obtain upper bound estimates for the lifespan of local solutions as byproduct of our iteration argument.