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日期精度:到日 2342 篇 · 到月 6077 篇 · 到年 470 篇 · 未提供 6 篇
Optimal Tests of Noncorrelation Between Multivariate Time Series
多元时间序列间不相关性的最优检验
The problem of testing noncorrelation between two multivariate time series is considered. Assuming that the global process admits a joint vector autoregressive (VAR) representation, noncorrelation between the two component series is equivalent to the hypothesis that all off-diagonal blocks in the matrix coefficients and the innovation covariance of the joint VAR representation are zero. We establish an adequate local asymptotic normality (LAN) property for this VAR model in…
Uniform Inference in Autoregressive Models
自回归模型中的一致有效推断
The purpose of this paper is to provide theoretical justification for some existing methods for constructing confidence intervals for the sum of coefficients in autoregressive models. We show that the methods of Stock (1991), Andrews (1993), and Hansen (1999) provide asymptotically valid confidence intervals, whereas the subsampling method of Romano and Wolf (2001) does not. In addition, we generalize the three valid methods to a larger class of statistics. We also clarify…
Efficiency of the California electricity reserves market
加州电力备用容量市场的效率
Abstract We test the efficiency of the California electricity reserves market by examining systematic differences between its day‐ and hour‐ahead prices. We uncover significant day‐ahead premia, which we attribute to market design characteristics. On the demand side, the market design established a principal–agent relationship between the markets' buyers (principal) and their supervisory authority (agent). The agent had very limited incentives to shift reserve purchases to…
Monte Carlo Estimation for Nonlinear Non-Gaussian State Space Models
非线性非高斯状态空间模型的蒙特卡洛估计
We develop a proposal or importance density for state space models with a nonlinear non-Gaussian observation vector y ∼ p(y¦θ) and an unobserved linear Gaussian signal vector θ ∼ p(θ). The proposal density is obtained from the Laplace approximation of the smoothing density p(θ¦y). We present efficient algorithms to calculate the mode of p(θ¦y) and to sample from the proposal density. The samples can be used for importance sampling and Markov chain Monte Carlo methods. The…
Simulation of hyper-inverse Wishart distributions in graphical models
图模型中超逆 Wishart 分布的模拟
We introduce and exemplify an efficient method for direct sampling from hyper-inverse Wishart distributions. The method relies very naturally on the use of standard junction-tree representation of graphs, and couples these with matrix results for inverse Wishart distributions. We describe the theory and resulting computational algorithms for both decomposable and nondecomposable graphical models. An example drawn from financial time series demonstrates application in a…
The high-dimension, low-sample-size geometric representation holds under mild conditions
高维小样本的几何表示在较弱条件下成立
High-dimension, low-small-sample size datasets have different geometrical properties from those of traditional low-dimensional data. In their asymptotic study regarding increasing dimensionality with a fixed sample size, Hall et al. (2005) showed that each data vector is approximately located on the vertices of a regular simplex in a high-dimensional space. A perhaps unappealing aspect of their result is the underlying assumption which requires the variables, viewed as a…
Simulation and inference for stochastic volatility models driven by Levy processes
Lévy 过程驱动的随机波动率模型:模拟与推断
We study Ornstein-Uhlenbeck stochastic processes driven by Lévy processes, and extend them to more general non-Ornstein-Uhlenbeck models. In particular, we investigate the means of making the correlation structure in the volatility process more flexible. For one model, we implement a method for introducing quasi long-memory into the volatility model. We demonstrate that the models can be fitted to real share price returns data.
Computer-intensive rate estimation, diverging statistics and scanning
计算密集型速率估计、发散统计量与扫描方法
A general rate estimation method is proposed that is based on studying the in-sample evolution of appropriately chosen diverging/converging statistics. The proposed rate estimators are based on simple least squares arguments, and are shown to be accurate in a very general setting without requiring the choice of a tuning parameter. The notion of scanning is introduced with the purpose of extracting useful subsamples of the data series; the proposed rate estimation method is…
Optimal rate of convergence for nonparametric change-point estimators for nonstationary sequences
非平稳序列非参数变点估计量的最优收敛速率
Let $( X_{i}) _{i=1,\ldots,n}$ be a possibly nonstationary sequence such that $\mathscr{L} (X_{i})=P_{n}$ if $i\leq n\theta $ and $\mathscr{L}(X_{i})=Q_{n}$ if $i \gt n\theta $, where $0 \lt \theta \lt 1$ is the location of the change-point to be estimated. We construct a class of estimators based on the empirical measures and a seminorm on the space of measures defined through a family of functions $\mathcal{F}$. We prove the consistency of the estimator and give rates of…
Asymptotic spectral theory for nonlinear time series
非线性时间序列的渐近谱理论
We consider asymptotic problems in spectral analysis of stationary causal processes. Limiting distributions of periodograms and smoothed periodogram spectral density estimates are obtained and applications to the spectral domain bootstrap are given. Instead of the commonly used strong mixing conditions, in our asymptotic spectral theory we impose conditions only involving (conditional) moments, which are easily verifiable for a variety of nonlinear time series.
An econometric analysis of asymmetric volatility: Theory and application to patents
Equilibrium Exhaustible Resource Price Dynamics
可耗竭资源价格的均衡动态
ABSTRACT We develop equilibrium models of exhaustible resource markets with endogenous extraction choices and prices. Our analysis demonstrates how adjustment costs can generate oil and gas forward price dynamics with two factors, consistent with the behavior these commodities exhibit in the Schwartz and Smith (2000) calibration. Our two‐factor model predicts that stochastic volatility will arise in these markets as a natural consequence of production adjustments, however,…
ON THE LAW OF LARGE NUMBERS FOR (GEOMETRICALLY) ERGODIC MARKOV CHAINS
遍历及几何遍历马尔可夫链的大数定律
For use in asymptotic analysis of nonlinear time series models, we show that with (Xt,t ≥ 0) a (geometrically) ergodic Markov chain, the general version of the strong law of large numbers applies. That is, the average converges almost surely to the expectation of φ(Xt,Xt+1,…) irrespective of the choice of initial distribution of, or value of, X0. In the existing literature, the less general form has been studied.We thank Paolo Paruolo (the co-editor) and the referee for…
A MODIFIED INFORMATION CRITERION FOR COINTEGRATION TESTS BASED ON A VAR APPROXIMATION
基于 VAR 近似的协整检验修正信息准则
We consider the cointegration tests of Johansen (1988, Journal of Economic Dynamics and Control 12, 231–254; 1991, Econometrica 59, 1551–1580) when a vector autoregressive (VAR) process of order k is used to approximate a more general linear process with a possibly infinite VAR representation. Traditional methods to select the lag order, such as Akaike's information criterion (AIC) or the Bayesian information criterion, often lead to too parsimonious a model with the…
THE LIKELIHOOD RATIO TEST FOR COINTEGRATION RANKS IN THE I(2) MODEL
I(2) 模型协整秩的似然比检验
This paper presents the likelihood ratio (LR) test for the number of cointegrating relations in the I(2) vector autoregressive model. It is shown that the asymptotic distribution of the LR test for the cointegration ranks is identical to the asymptotic distribution of the much applied test statistic based on the two-step estimation procedure in Johansen (1995, Econometric Theory 11, 25–59), Paruolo (1996, Journal of Econometrics 72, 313–356), and Rahbek, Kongsted, and…
FINITE-SAMPLE PROPERTIES OF FORECASTS FROM THE STATIONARY FIRST-ORDER AUTOREGRESSIVE MODEL UNDER A GENERAL ERROR DISTRIBUTION
一般误差分布下平稳一阶自回归模型预测的有限样本性质
We study the properties of the multi-period-ahead least-squares forecast for the stationary AR(1) model under a general error distribution. We find that the forecast is unbiased up to O(T−1), where T is the in-sample size, regardless of the error distribution and that the mean squared forecast error, up to O(T−3/2), is robust against nonnormality.The author is grateful to the co-editor Paolo Paruolo and two anonymous referees for helpful comments. The author is solely…
THE AVAILABLE INFORMATION FOR INVARIANT TESTS OF A UNIT ROOT
单位根不变检验的可用信息
This paper considers the information available to invariant unit root tests at and near the unit root. Because all invariant tests will be functions of the maximal invariant, the Fisher information in this statistic will be the available information. The main finding of the paper is that the available information for all tests invariant to a linear trend is zero at the unit root. This result applies for any sample size, over a variety of distributions and correlation…
REGRESSION WITH SLOWLY VARYING REGRESSORS AND NONLINEAR TRENDS
缓慢变化回归变量与非线性趋势回归
Slowly varying (SV) regressors arise commonly in empirical econometric work, particularly in the form of semilogarithmic regression and log periodogram regression. These regressors are asymptotically collinear. Usual regression formulas for asymptotic standard errors are shown to remain valid, but rates of convergence are affected and the limit distribution of the regression coefficients is shown to be one dimensional. Some asymptotic representations of partial sums of SV…
Asymmetric power distribution: Theory and applications to risk measurement
非对称幂分布:理论及风险度量应用
Abstract Theoretical literature in finance has shown that the risk of financial time series can be well quantified by their expected shortfall, also known as the tail value‐at‐risk. In this paper, I construct a parametric estimator for the expected shortfall based on a flexible family of densities, called the asymmetric power distribution (APD). The APD family extends the generalized power distribution to cases where the data exhibits asymmetry. The first contribution of the…
Asymptotic expansions for sums of block-variables under weak dependence
弱依赖下区块变量和的渐近展开
Let {Xi}i=−∞∞ be a sequence of random vectors and $Y_{in}=f_{in}(\mathcal{X}_{i,\ell})$ be zero mean block-variables where $\mathcal{X}_{i,\ell}=(X_{i},\ldots,X_{i+\ell-1})$, i≥1, are overlapping blocks of length ℓ and where fin are Borel measurable functions. This paper establishes valid joint asymptotic expansions of general orders for the joint distribution of the sums ∑i=1nXi and ∑i=1nYin under weak dependence conditions on the sequence {Xi}i=−∞∞ when the block length ℓ…
Accumulated prediction errors, information criteria and optimal forecasting for autoregressive time series
累积预测误差、信息准则与自回归时间序列的最优预测
The predictive capability of a modification of Rissanen’s accumulated prediction error (APE) criterion, APEδn, is investigated in infinite-order autoregressive (AR(∞)) models. Instead of accumulating squares of sequential prediction errors from the beginning, APEδn is obtained by summing these squared errors from stage nδn, where n is the sample size and 1/n≤δn≤1−(1/n) may depend on n. Under certain regularity conditions, an asymptotic expression is derived for the…
Testing for change points in time series models and limiting theorems for NED sequences
时间序列模型的变点检验与近历依赖序列的极限定理
This paper first establishes a strong law of large numbers and a strong invariance principle for forward and backward sums of near-epoch dependent sequences. Using these limiting theorems, we develop a general asymptotic theory on the Wald test for change points in a general class of time series models under the no change-point hypothesis. As an application, we verify our assumptions for the long-memory fractional ARIMA model.
Estimation of impulse response functions using long autoregression
利用长自回归估计脉冲响应函数
This article proposes an alternative methodology to estimate impulse response functions without imposing parametric restrictions. The impulse responses are estimated by regressing the series of interest on estimated innovations, which are the residuals obtained from a prior-stage "long autoregression." We establish the consistency and asymptotic normality of the proposed estimator. Copyright Royal Economic Society 2007