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电价的状态转换长记忆模型AI 解读

In this paper we develop a regime switching model which can generate long memory (fractional integration) in each of the regime states. This property is relevant in a number of cases. For instance, the deregulated market for electricity power in the Nordic countries is characterized by electricity spot prices with a high degree of long memory. It occurs that in some time periods bilateral prices are identical whereas in other periods the prices differ. The latter occurs when…

VAR 模型中协整秩检验与选择的自助法算法AI 解读

In this paper a bootstrap algorithm for a reduced rank vector autoregressive model with a restricted linear trend and independent, identically distributed errors is analyzed. For testing the cointegration rank, the asymptotic distribution under the hypothesis is the same as for the usual likelihood ratio test, so that the bootstrap is consistent. It is furthermore shown that a bootstrap procedure for determining the rank is asymptotically consistent in the sense that the…

条件预测能力检验AI 解读

We propose a framework for out-of-sample predictive ability testing and forecast selection designed for use in the realistic situation in which the forecasting model is possibly misspecified, due to unmodeled dynamics, unmodeled heterogeneity, incorrect functional form, or any combination of these. Relative to the existing literature (Diebold and Mariano (1995) and West (1996)), we introduce two main innovations: (i) We derive our tests in an environment where the finite…

线性与非线性自回归模型的有效预测AI 解读

Conditional expectations given past observations in stationary time series are usually estimated directly by kernel estimators, or by plugging in kernel estimators for transition densities. We show that, for linear and nonlinear autoregressive models driven by independent innovations, appropriate smoothed and weighted von Mises statistics of residuals estimate conditional expectations at better parametric rates and are asymptotically efficient. The proof is based on a…

条件异方差时间序列的准极大似然估计：随机递推方程方法AI 解读

This paper studies the quasi-maximum-likelihood estimator (QMLE) in a general conditionally heteroscedastic time series model of multiplicative form Xt=σtZt, where the unobservable volatility σt is a parametric function of (Xt−1, …, Xt−p, σt−1, …, σt−q) for some p, q≥0, and (Zt) is standardized i.i.d. noise. We assume that these models are solutions to stochastic recurrence equations which satisfy a contraction (random Lipschitz coefficient) property. These assumptions are…

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回归系数一般持续性时变的有效检验AI 解读

There are a large number of tests for instability or breaks in coefficients in regression models designed for different possible departures from the stable model. We make two contributions to this literature. First, we consider a large class of persistent breaking processes that lead to asymptotically equivalent efficient tests. Our class allows for many or relatively few breaks, clustered breaks, regularly occurring breaks, or smooth transitions to changes in the regression…

短时段内协整关系失效的检验AI 解读

This article introduces tests for cointegration breakdown that may occur over a relatively short time period, such as at the end of the sample. The breakdown may be due to a shift in the cointegrating vector or due to a shift in the errors from being I(0) to being I(1). Tests are introduced based on the postbreakdown sum of squared residuals and sum of squared reverse partial sums of residuals. Critical values are provided using a subsampling method. Asymptotic results take…

不平衡协整AI 解读

Recently, increasing interest in the issue of fractional cointegration has emerged from theoretical and empirical viewpoints. Here, as opposed to the traditional prescription of unit root observables with weak dependent cointegrating errors, the orders of integration of these series are allowed to take real values, but, as in the traditional framework, equality of the orders of at least two observable series is necessary for cointegration. This assumption, in view of the…

不增加方差的长记忆参数偏差缩减对数周期图与 Whittle 估计AI 解读

The bias-reduced log-periodogram estimator of Andrews and Guggenberger (2003, Econometrica 71, 675–712) for the long-memory parameter d in a stationary long-memory time series reduces the asymptotic bias of the original log-periodogram estimator of Geweke and Porter-Hudak (1983) by an order of magnitude but inflates the asymptotic variance by a multiplicative constant cr, for example, c1 = 2.25 and c2 = 3.52. In this paper, we introduce a new, computationally attractive…

无需观测过程矩假设的一般 GARCH(1,1) 模型混合性质AI 解读

We consider general, and possibly nonparametric, GARCH(1,1) processes. First we give conditions for the existence and the uniqueness of stationary ergodic solutions. Then we identify additional conditions for geometric ergodicity. These conditions consist of mild restrictions on the distribution of the latent independent process. No moment assumption is made on the generalized autoregressive conditionally heteroskedastic (GARCH) process. Applications to the asymptotic…

《多元时间序列分析新导论》书籍评介AI 解读

Vector time series analysis has become a standard tool in macroeconometrics and in empirical finance since the early 1980s. Over the last two decades, Helmut Lütkepohl has published extensively on virtually all topics covered in this book, which puts him in an excellent position for writing an authoritative textbook on this subject.

非平稳自回归过程的相关图AI 解读

Summary Analysis of time series often involves correlograms and partial correlograms as graphical descriptions of temporal dependence. Two methods are available for computing these statistics: one based on autocorrelations and the other on scaled autocovariances. For a stationary time series the resulting plots are nearly identical. When it comes to time series exhibiting non-stationary features these methods can lead to very different results. This has two consequences:…

演化小波谱的 Haar–Fisz 估计AI 解读

Summary We propose a new ‘Haar–Fisz’ technique for estimating the time-varying, piecewise constant local variance of a locally stationary Gaussian time series. We apply our technique to the estimation of the spectral structure in the locally stationary wavelet model. Our method combines Haar wavelets and the variance stabilizing Fisz transform. The resulting estimator is mean square consistent, rapidly computable and easy to implement, and performs well in practice. We also…

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鞅差假设的广义谱检验AI 解读

This article proposes a test for the Martingale Difference Hypothesis (MDH) using depen- dence measures related to the characteristic function. The MDH typically has been tested using the sample autocorrelations or in the spectral domain using the periodogram. Tests based on these statistics are inconsistent against uncorrelated non-martingales processes. Here, we gen- eralize the spectral test of Durlauf (1991) for testing the MDH taking into account linear and nonlinear…

无需一致估计渐近协方差矩阵的稳健 M 检验AI 解读

We extend the KVB approach of Kiefer, Vogelsang, and Bunzel (2000) to constructing robust M tests without consistent estimation of the asymptotic covariance matrix. We demonstrate that, when model parameters have to be estimated, the normalizing matrix computed using a full-sample estimator is able to eliminate the nuisance parameters when there is no estimation effect but not otherwise. To circumvent the problem of estimation effect, we propose using recursive estimators to…

分位数自回归AI 解读

We consider quantile autoregression (QAR) models in which the autoregressive coefficients can be expressed as monotone functions of a single, scalar random variable. The models can capture systematic influences of conditioning variables on the location, scale, and shape of the conditional distribution of the response, and thus constitute a significant extension of classical constant coefficient linear time series models in which the effect of conditioning is confined to a…

用边际积分估计和检验加性模型中的变系数AI 解读

We propose marginal integration estimation and testing methods for the coefficients of varying-coefficient multivariate regression models. Asymptotic distribution theory is developed for the estimation method, which enjoys the same rate of convergence as univariate function estimation. For the test statistic, asymptotic normal theory is established. These theoretical results are derived under the fairly general conditions of absolute regularity (β-mixing). Application of the…

用二元混合转移分布模型刻画带标记点过程AI 解读

We propose new probability models for the analysis of marked point processes. These models deal with the type of data that arrive or are observed in possibly unequal time intervals, such as financial transactions and earthquakes, among others. The models treat both the time between event arrivals and the observed marks as stochastic processes. We adopt a class of bivariate distributions to form the bivariate mixture transition distribution. In these models the conditional…