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正态混合 GARCH(1,1)：汇率建模应用AI 解读

Abstract Some recent specifications for GARCH error processes explicitly assume a conditional variance that is generated by a mixture of normal components, albeit with some parameter restrictions. This paper analyses the general normal mixture GARCH(1,1) model which can capture time variation in both conditional skewness and kurtosis. A main focus of the paper is to provide evidence that, for modelling exchange rates, generalized two‐component normal mixture GARCH(1,1)…

跨期定价与价格歧视：个人电脑市场的半参数特征价格分析AI 解读

Abstract We apply a smooth coefficient semiparametric model to a unique high‐frequency data set to examine the intertemporal pricing of personal computers. Furthermore, we test whether firms charge differential component prices for their top performance personal computers and whether premium firms charge both a premium for all their computers and a premium for their top performance ones. We find nonlinear effects in the pricing of personal computer components. We also find…

分组数据下的稳健与有效估计AI 解读

The minimum Hellinger distance estimator is known to have desirable properties in terms of robustness and efficiency. We propose an approximate minimum Hellinger distance estimator by adapting the approach to grouped data from a continuous distribution. It is easier to compute the approximate version for either the continuous data or the grouped data. Given certain conditions on the model distribution and reasonable grouping rules, the approximate minimum Hellinger distance…

结构测量误差模型中的潜变量模型稳健性AI 解读

We present methods for diagnosing the effects of model misspecification of the true-predictor distribution in structural measurement error models. We first formulate latent-model robustness theoretically. Then we provide practical techniques for examining the adequacy of an assumed latent predictor model. The methods are illustrated via analytical examples, application to simulated data and with data from a study of coronary heart disease.

谱密度的收缩估计量AI 解读

We propose a shrinkage estimator for spectral densities based on a multilevel normal hierarchical model. The first level captures the sampling variability via a likelihood constructed using the asymptotic properties of the periodogram. At the second level, the spectral density is shrunk towards a parametric time series model. To avoid selecting a particular parametric model for the second level, a third level is added which induces an estimator that averages over a class of…

异方差部分线性模型的有效半参数估计量AI 解读

We study the heteroscedastic partially linear model with an unspecified partial baseline component and a nonparametric variance function. An interesting finding is that the performance of a naive weighted version of the existing estimator could deteriorate when the smooth baseline component is badly estimated. To avoid this, we propose a family of consistent estimators and investigate their asymptotic properties. We show that the optimal semiparametric efficiency bound can…

利用片内协方差改进回归中心子空间估计AI 解读

Popular methods for estimating the central subspace in regression require slicing a continuous response. However, slicing can result in loss of information and in some cases that loss can be substantial. We use intraslice covariances to construct improved inference methods for the central subspace. These methods are optimal within a class of quadratic inference functions and permit chi-squared tests of conditional independence hypotheses involving the predictors. Our…

删失数据的最小二乘回归AI 解读

The semiparametric accelerated failure time model relates the logarithm of the failure time linearly to the covariates while leaving the error distribution unspecified. The present paper describes simple and reliable inference procedures based on the least-squares principle for this model with right-censored data. The proposed estimator of the vector-valued regression parameter is an iterative solution to the Buckley–James estimating equation with a preliminary consistent…

基于多项式系数密度的聚合AR(1)模型AI 解读

This paper develops a new kind of aggregation model. We extend the work of Linden (1999) to allow the AR coefficient to be drawn from a polynomial density function. The polynomial density incorporates a wealth of multi-modal density functions as special cases. Given the aggregate data, we provide estimation methods for the coefficients and the order of the polynomial density. A test for the functional form of the polynomial is provided. We apply the model to the consumption…

回归误差方差估计中预检验最优临界值的进一步结果AI 解读

This paper enlarges on results of Wan and Zou (Journal of Econometrics 114 (2003), 165--96) on the choice of critical values for pre-test procedures based on the minimum risk criterion. We consider a modification of the general theorem given in Wan and Zou (2003) to obtain the optimal critical value that minimizes the risks of various inequality pre-test estimators of the regression error variance under a general class of first-order differentiable loss functions.…

异质面板平稳性的均值组检验AI 解读

This paper proposes a panel-based mean group test for the null of stationarity against the alternative of unit roots in the presence of both heterogeneity across cross-section units and serial correlation across time periods. Using both sequential and joint asymptotic analyses the proposed test statistic is shown to be distributed as standard normal under the null for large N (number of groups) and large T (number of time periods). Monte Carlo results support the use of…

线性回归异方差的模拟检验：进一步结果AI 解读

As shown by the results of Dufour, Khalaf, Bernard and Genest (2004, Journal of Econometrics 122, 317--347), exact tests for heteroskedasticity in linear regression models can be obtained, by using Monte Carlo (MC) techniques, if either (i) it is assumed that the true form of the error distribution under homoskedasticity is known, or (ii) the null hypothesis specifies both homoskedasticity and the form of the error distribution. Non-parametric bootstrap tests of…

矩条件选择的自助法AI 解读

This paper proposes a bootstrap-based procedure for selecting the best moment conditions among a set of correctly specified moment conditions. The proposed method can be motivated by Edgeworth expansions and chooses moment conditions that minimize the approximate coverage error of confidence intervals and hypothesis tests for parameters. Because of the analytical intractability of Edgeworth expansions, we estimate the coverage error by the bootstrap. The proposed method can…

金融因子、宏观信息与利率期限结构的预期理论AI 解读

In this paper we develop on the VAR framework, originally proposed by Campbell and Shiller (J. Political Econom 95 (1987) 1062) to evaluate the Expectations Theory, along three dimensions: the use of a testing method based on a real-time procedure, the measurement of the risk premium, the specification of the implicit monetary policy maker’s reaction function. We use financial factors and macroeconomic information to construct a test of the theory based on simulating…

不同计量设定下风险的期限结构AI 解读

This paper characterizes the term structure of risk measures such as value at risk (VaR) and expected shortfall under different econometric approaches including multivariate regime switching, GARCH-in-mean models with Student-t errors, two-component GARCH models and a nonparametric bootstrap. We show how to derive the risk measures for each of these models and document large variations in term structures across econometric specifications. An out-of-sample forecasting…

含重复测量的 cDNA 微阵列：质量控制与稳健估计AI 解读

We consider robust estimation of gene intensities from cDNA microarray data with replicates. Several statistical methods for estimating gene intensities from microarrays have been proposed, but little work has been done on robust estimation. This is particularly relevant for experiments with replicates, because even one outlying replicate can have a disastrous effect on the estimated intensity for the gene concerned. Because of the many steps involved in the experimental…

遗传关联研究中单倍型效应的似然推断AI 解读

A haplotype is a specific sequence of nucleotides on a single chromosome. The population associations between haplotypes and disease phenotypes provide critical information about the genetic basis of complex human diseases. Standard genotyping techniques cannot distinguish the two homologous chromosomes of an individual, so only the unphased genotype (i.e., the combination of the two homologous haplotypes) is directly observable. Statistical inference about…

混合线性模型的高崩溃点稳健推断AI 解读

Mixed linear models are used to analyze data in many settings. These models have a multivariate normal formulation in most cases. The maximum likelihood estimator (MLE) or the residual MLE (REML) is usually chosen to estimate the parameters. However, the latter are based on the strong assumption of exact multivariate normality. Welsh and Richardson have shown that these estimators are not robust to small deviations from multivariate normality. This means that in practice a…

基于 Fiducial 枢轴量的广义置信区间AI 解读

Generalized pivotal quantities (GPQs) and generalized confidence intervals (GCIs) have proven to be useful tools for making inferences in many practical problems. Although GCIs are not guaranteed to have exact frequentist coverage, a number of published and unpublished simulation studies suggest that the coverage probabilities of such intervals are sufficiently close to their nominal value so as to be useful in practice. In this article we single out a subclass of…

伯努利网格中最长显著游程长度的分布及应用AI 解读

We consider the length of the longest significance run in a (two-dimensional) Bernoulli net and derive its asymptotic limit distribution. Our results can be considered as generalizations of known theorems in significance runs. We give three types of theoretical results: (1) reliability-style lower and upper bounds, (2) Erdös–Rényi law, and (3) the asymptotic limit distribution. To understand the rate of convergence to the asymptotic distributions, we carry out numerical…

稳健贝叶斯分析的样本量确定AI 解读

This article considers a robust Bayesian approach to the sample size determination problem. We focus on global Bayesian robustness that studies lower bound (Ln), upper bound (Un), and range (Rn) of posterior quantities of interest, obtained as the prior varies in a class of distributions. Specifically, we are interested in the selection of an appropriate sample size that gives guarantees to the researcher of observing a small value of the range and, depending on the…

有限总体域均值的估计AI 解读

In this article we introduce a general methodology for producing a model-assisted empirical best predictor (EBP) of a finite population domain mean using data from a complex survey. Our method improves on the commonly used design-consistent survey estimator by using a suitable mixed model. Such a model combines information from related sources, such as census and administrative data. Unlike a purely model-based EBP, the proposed model-assisted EBP converges in probability to…

通过函数型数据预平滑改进相异度估计AI 解读

We examine the effect of presmoothing functional data on estimating the dissimilarities among objects in a dataset, with applications to cluster analysis and other distance methods, such as multidimensional scaling and statistical matching. We prove that a shrinkage method of smoothing results in a better estimator of the dissimilarities among a set of noisy curves. For a model with independent noise structure, the smoothed-data dissimilarity estimator dominates the…

监督主成分预测AI 解读

In regression problems where the number of predictors greatly exceeds the number of observations, conventional regression techniques may produce unsatisfactory results. We describe a technique called supervised principal components that can be applied to this type of problem. Supervised principal components is similar to conventional principal components analysis except that it uses a subset of the predictors selected based on their association with the outcome. Supervised…