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ON THE TAIL BEHAVIORS OF A FAMILY OF GARCH PROCESSES

一类 GARCH 过程的尾部行为

In this paper, some structural properties of a family of generalized autoregressive conditionally heteroskedastic (GARCH) processes are considered. First, a sufficient and necessary condition for the strict stationarity of this family of GARCH processes is given. Second, some simple conditions for the existence of the moments of the family of GARCH processes are also derived. Finally, we describe the tail of the marginal distribution of the family of GARCH processes.I am…

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MIXING PROPERTIES OF A GENERAL CLASS OF GARCH(1,1) MODELS WITHOUT MOMENT ASSUMPTIONS ON THE OBSERVED PROCESS

无需观测过程矩假设的一般 GARCH(1,1) 模型混合性质

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…

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NEW INTRODUCTION TO MULTIPLE TIME SERIES ANALYSIS , by Helmut Lütkepohl, Springer, 2005

《多元时间序列分析新导论》书籍评介

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.

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A Haar–Fisz technique for locally stationary volatility estimation

用于局部平稳波动率估计的 Haar–Fisz 技术

We consider a locally stationary model for financial log-returns whereby the returns are independent and the volatility is a piecewise-constant function with jumps of an unknown number and locations, defined on a compact interval to enable a meaningful estimation theory. We demonstrate that the model explains well the common characteristics of log-returns. We propose a new wavelet thresholding algorithm for volatility estimation in this model, in which Haar wavelets are…

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Correlograms for Non-Stationary Autoregressions

非平稳自回归过程的相关图

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:…

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Haar–Fisz Estimation of Evolutionary Wavelet Spectra

演化小波谱的 Haar–Fisz 估计

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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Generalized spectral tests for the martingale difference hypothesis

鞅差假设的广义谱检验

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…

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Robust M Tests Without Consistent Estimation of the Asymptotic Covariance Matrix

无需一致估计渐近协方差矩阵的稳健 M 检验

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…

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Quantile Autoregression

分位数自回归

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…

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Estimation and Testing for Varying Coefficients in Additive Models With Marginal Integration

用边际积分估计和检验加性模型中的变系数

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…

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Modeling Marked Point Processes via Bivariate Mixture Transition Distribution Models

用二元混合转移分布模型刻画带标记点过程

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…

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Bayesian Inference for a Two-Part Hierarchical Model

两部分层级模型的贝叶斯推断

Profiling is currently an important, and hotly debated, topic in health care and other industries looking for ways to control costs, increase profitability, and increase service quality. Managed care in particular has seen a proliferation in the use of statistical profiling methodology, particularly with regard to monitoring expenditure data. This article focuses on the specific problem of developing statistical methods appropriate for profiling physician contributions to…

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How quickly do forecasters incorporate news? Evidence from cross‐country surveys

预测者多快吸收新信息?跨国调查证据

Abstract Using forecasts from Consensus Economics Inc., we provide evidence on the efficiency of real GDP growth forecasts by testing whether forecast revisions are uncorrelated. As the forecast data used are multi‐dimensional—18 countries, 24 monthly forecasts for the current and the following year and 16 target years—the panel estimation takes into account the complex structure of the variance–covariance matrix due to propagation of shocks across countries and economic…

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A small monetary system for the euro area based on German data

基于德国数据的欧元区小型货币系统

Abstract Previous euro area money demand studies have used aggregated national time series data from the countries participating in the European Monetary Union (EMU). However, aggregation may be problematic because macroeconomic convergence processes have taken place in the countries of interest. Therefore, in this study, quarterly German data until 1998 are combined with data from the euro area from 1999 until 2002 and these series are used for fitting a small vector error…

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Efficient likelihood estimation in state space models

状态空间模型中的有效似然估计

Motivated by studying asymptotic properties of the maximum likelihood estimator (MLE) in stochastic volatility (SV) models, in this paper we investigate likelihood estimation in state space models. We first prove, under some regularity conditions, there is a consistent sequence of roots of the likelihood equation that is asymptotically normal with the inverse of the Fisher information as its variance. With an extra assumption that the likelihood equation has a unique root…

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ANOVA for diffusions and Itô processes

扩散过程与Itô过程的方差分析

Itô processes are the most common form of continuous semimartingales, and include diffusion processes. This paper is concerned with the nonparametric regression relationship between two such Itô processes. We are interested in the quadratic variation (integrated volatility) of the residual in this regression, over a unit of time (such as a day). A main conceptual finding is that this quadratic variation can be estimated almost as if the residual process were observed, the…

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Asymptotic equivalence of nonparametric autoregression and nonparametric regression

非参数自回归与非参数回归的渐近等价性

It is proved that nonparametric autoregression is asymptotically equivalent in the sense of Le Cam’s deficiency distance to nonparametric regression with random design as well as with regular nonrandom design.

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