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加权重复中位数平滑与滤波AI 解读

We propose weighted repeated median filters and smoothers for robust nonparametric regression in general and for robust online signal extraction from time series in particular. The new methods allow us to remove outlying sequences and to preserve discontinuities (shifts) in the underlying regression function (the signal) in the presence of local linear trends. Suitable weighting of the observations according to their distances in the design space reduces the bias arising…

Brock–Dechert–Scheinkman检验的秩扩展AI 解读

This article proposes new tests of randomness for innovations in a large class of time series models. These tests are based on functionals of empirical processes constructed from either the model residuals or their associated ranks. The asymptotic behavior of these processes is determined under the null hypothesis of randomness. The limiting distributions are seen to be independent of estimation errors under appropriate regularity conditions. Several test statistics are…

非参数函数估计的非平衡Haar技术AI 解读

The discrete unbalanced Haar (UH) transform is a decomposition of one-dimensional data with respect to an orthonormal Haar-like basis where jumps in the basis vectors do not necessarily occur in the middle of their support. We introduce a multiscale procedure for estimation in Gaussian noise that consists of three steps: a UH transform, thresholding of the decomposition coefficients, and the inverse UH transform. We show that our estimator is mean squared consistent with…

非齐次泊松过程的贝叶斯预测及呼叫中心应用AI 解读

A call center is a centralized hub where customer and other telephone calls are handled by an organization. In today's economy, call centers have become the primary points of contact between customers and businesses. Thus accurate predictions of call arrival rates are indispensable to help call center practitioners staff their call centers efficiently and cost-effectively. This article proposes a multiplicative model for modeling and forecasting within-day arrival rates to a…

未知损失函数下的预测最优性检验AI 解读

Empirical tests of forecast optimality have traditionally been conducted under the assumption of mean squared error loss or some other known loss function. In this article we establish new testable properties that hold when the forecaster's loss function is unknown but testable restrictions can be imposed on the data-generating process, trading off conditions on the data-generating process against conditions on the loss function. We propose flexible estimation of the…

函数型观测独立性的 Portmanteau 综合检验AI 解读

In various fields, observations are curves over some natural time interval. These curves often arise from finely spaced measurements (e.g., in physical sciences and finance) or from smoothing unequally spaced sparse measurements. Recent years have seen the development of tools for analyzing such data in the growing field of functional data analysis. To validate the assumptions underlying these tools, it is important to verify that the functional observations form a simple…

差分AR(1)过程协方差矩阵的行列式AI 解读

In this note, determinants are explicitly calculated for the covariance matrices of differenced and double-differenced AR(1) variables.The author thanks Peter C.B. Phillips for introducing the author to Grenander and Szegö's book on Toeplitz matrices and giving useful comments. The author also thanks two anonymous referees for helpful comments on earlier drafts of the note.

分数单整过程的长期协方差矩阵AI 解读

An asymptotic expansion is given for the autocovariance matrix of a vector of stationary long-memory processes with memory parameters d ∈ [0,½). The theory is then applied to deliver formulas for the long-run covariance matrices of multivariate time series with long memory.Phillips acknowledges partial support from a Kelly Fellowship and from the NSF under grant SES 04-142254. This may be proved directly using a Fourier integral asymptotic expansion when the spectrum of the…

存在多次水平突变的自回归单位根检验AI 解读

The asymptotic distributions of augmented Dickey–Fuller (ADF) unit root tests for autoregressive processes with a unit or near-unit root are discussed in the presence of multiple stochastic level shifts of large size occurring independently in time. The distributions depend on a Brownian motion and a Poisson-type jump process. Due to the latter, tests based on standard critical values experience power losses increasing rapidly with the number and the magnitude of the shifts.…

检测单位根与平稳性的序贯监测程序AI 解读

When analyzing time series an important issue is to decide whether the time series is stationary or a random walk. Relaxing these notions, we consider the problem to decide in favor of the I(0) or I(1) property. Fixed-sample statistical tests for that problem are well studied in the literature. In this paper we provide first results for the problem of monitoring sequentially a time series. Our stopping times are based on a sequential version of a kernel-weighted…

现值关系、格兰杰非因果性与VAR稳定性AI 解读

When in the class of “exact” present value (PV) relations the decision variables do not Granger cause the explanatory variables, and a vector autoregressive (VAR) process is used to derive the cross-equation restrictions, the system embodies explosive roots, which hardly can be reconciled with the typical features observed in most macroeconomic time series. This paper investigates the issue.I thank Paolo Paruolo and two anonymous referees for helpful comments and suggestions…

回归误设时GLS在RegARIMA及相关模型一步预测中的最优性AI 解读

We consider the modeling of a time series described by a linear regression component whose regressor sequence satisfies the generalized asymptotic sample second moment stationarity conditions of Grenander (1954, Annals of Mathematical Statistics 25, 252–272). The associated disturbance process is only assumed to have sample second moments that converge with increasing series length, perhaps after a differencing operation. The model's regression component, which can be…

动态系统中的协整搜索AI 解读

, which can be zero, stable cointegrating vectors against the alternative hypothesis of more than r0 cointegrating vectors existing in some subsample. The tests proposed follow Breitung (2002). They are non-parametric in nature and are invariant to linear transformations of the series. A distinctive feature is that they allow us to detect the hidden cointegration when the system is affected by an unknown number of regime changes of unknown timing. We analyse the limiting…

波动率非对称建模：树结构多元 GARCH 模型的贝叶斯分析AI 解读

A new class of multivariate threshold GARCH models is proposed for the analysis and modelling of volatility asymmetries in financial time series. The approach is based on the idea of a binary tree where every terminal node parametrizes a (local) multivariate GARCH model for a specific partition of the data. A Bayesian stochastic method is developed and presented for the analysis of the proposed model consisting of parameter estimation, model selection and volatility…

状态切换检验AI 解读

We analyze use of a quasi-likelihood ratio statistic for a mixture model to test the null hypothesis of one regime versus the alternative of two regimes in a Markov regime-switching context. This test exploits mixture properties implied by the regime-switching process, but ignores certain implied serial correlation properties. When formulated in the natural way, the setting is nonstandard, involving nuisance parameters on the boundary of the parameter space, nuisance…

转型建模与计量收敛检验AI 解读

A new panel data model is proposed to represent the behavior of economies in transition allowing for a wide range of possible time paths and individual heterogeneity. The model has both common and individual specific components and is formulated as a nonlinear time varying factor model. When applied to a micro panel, the decomposition provides flexibility in idiosyncratic behavior over time and across section, while retaining some commonality across the panel by means of an…

基于变换的鞅估计函数AI 解读

An estimation method is proposed for a wide variety of discrete time stochastic processes that have an intractable likelihood function but are otherwise conveniently specified by an integral transform such as the characteristic function, the Laplace transform or the probability generating function. This method involves the construction of classes of transform-based martingale estimating functions that fit into the general framework of quasi-likelihood. In the parametric…

强依赖下近不稳定过程最小二乘估计量的渐近理论AI 解读

This paper considers the effect of least squares procedures for nearly unstable linear time series with strongly dependent innovations. Under a general framework and appropriate scaling, it is shown that ordinary least squares procedures converge to functionals of fractional Ornstein–Uhlenbeck processes. We use fractional integrated noise as an example to illustrate the important ideas. In this case, the functionals bear only formal analogy to those in the classical…

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非对称损失与非线性下最优预测的性质AI 解读

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted under the assumption of mean squared error loss. Under this loss function optimal forecasts should be unbiased and forecast errors serially uncorrelated at the single period horizon with increasing variance as the forecast horizon grows. Using analytical results we show in this paper that all the standard properties of optimal forecasts can be invalid under asymmetric loss and…

摘要暂缺

平稳分数协整的局部 Whittle 分析及隐含与已实现波动率的关系AI 解读

I consider local Whittle analysis of a stationary fractionally cointegrated model. The local Whittle quasi maximum likelihood estimator is proposed to jointly estimate the integration orders of the regressors, the integration order of the errors, and the cointegration vector. The proposed estimator is semiparametric in the sense that it employs local assumptions on the joint spectral density matrix of the regressors and the errors near the zero frequency. I show that the…

长记忆模型中遗漏非线性的检验AI 解读

This article constructs tests for the presence of nonlinearity of unknown form in addition to a fractionally integrated, long-memory component in a time series process. The tests are based on artificial neural network approximations and do not restrict the parametric form of the nonlinearity. Some theoretical results for the new tests are obtained, and detailed simulation evidence on the power of the tests is presented. The new methodology is then applied to a wide variety…

长面板协整模型的统计推断AI 解读

This article presents a general likelihood-based framework for inference in panel vector autoregressive (VAR) models with cointegration restrictions. The cointegrating relationships are restricted to each cross section while the rest of the model is unrestricted. The homogeneous restriction of common cointegrating space is also considered. Asymptotic distributions of parameter estimators and the test statistics for the cointegrating rank and the homogeneous restriction are…