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理解即期与远期汇率回归AI 解读

Using the Kalman filter, we obtain maximum likelihood estimates of a permanent-transitory components model for log spot and forward dollar prices of the pound, the franc, and the yen. This simple parametric model is useful in understanding why the forward rate may be an unbiased predictor of the future spot rate even though an increase in the forward premium predicts a dollar appreciation. Our estimates of the expected excess return on short-term dollar-denominated assets…

金融利差能否预测欧盟国家的通胀与产出增长？AI 解读

This paper seeks to address the policy issue of the usefulness of financial spreads as indicators of future inflation and output growth in the countries of the European Union, placing a particular focus on out-of-sample forecasting performance. Such analysis is of considerable relevance to monetary authorities, given the breakdown of the money/income relation in a number of countries and following increased emphasis of domestic monetary policy on control of inflation…

金融利差能否预测欧盟国家的通胀与产出增长？AI 解读

This paper seeks to address the policy issue of the usefulness of financial spreads as indicators of future inflation and output growth in the countries of the European Union, placing a particular focus on out-of-sample forecasting performance. Such analysis is of considerable relevance to monetary authorities, given the breakdown of the money/income relation in a number of countries and following increased emphasis of domestic monetary policy on control of inflation…

理解即期与远期汇率回归AI 解读

Using the Kalman filter, we obtain maximum likelihood estimates of a permanent-transitory components model for log spot and forward dollar prices of the pound, the franc, and the yen. This simple parametric model is useful in understanding why the forward rate may be an unbiased predictor of the future spot rate even though an increase in the forward premium predicts a dollar appreciation. Our estimates of the expected excess return on short-term dollar-denominated assets…

自回归过程均值的有保证估计AI 解读

This paper considers the problem of sequential point estimation of the mean of a stable autoregressive process with unknown scale and autoregressive parameters. The construction of a sequential procedure makes use of special stopping rules and some modifications of least-squares estimates. The procedure enables estimating the mean with prescribed mean-square accuracy uniformly in nuisance parameters. The uniform asymptotic normality and the asymptotic minimaxity of the…

分布变化最优检测札记AI 解读

Suppose $X_1, X_2, \dots, X_{\nu - 1}$ are iid random variables with distribution $F_0$, and $X_{\nu}, X_{\nu + 1}, \dots$ are are iid with distributed $F_1$. The change point $\nu$ is unknown. The problem is to raise an alarm as soon as possible after the distribution changes from $F_0$ to $F_1$ (detect the change), but to avoid false alarms. Pollak found a version of the Shiryayev-Roberts procedure to be asymptotically optimal for the problem of minimizing the average run…

弱相依过程的经验似然方法AI 解读

This paper studies the method of empirical likelihood in models with weakly dependent processes. In such cases, if the likelihood function is formulated as if the data process were independent, obviously empirical likelihood fails. We propose to use empirical likelihood of blocks of observations to solve this problem in a nonparametric manner. This method of "blockwise empirical likelihood" preserves the dependence of data, and the resulting likelihood ratios can be used to…

相关误差下非参数回归的大样本推断AI 解读

A central limit theorem is given for certain weighted partial sums of a covariance stationary process, assuming it is linear in martingale differences, but without any restriction on its spectrum. We apply the result to kernel nonparametric fixed-design regression, giving a single central limit theorem which indicates how error spectral behavior at only zero frequency influences the asymptotic distribution and covers long-range, short-range and negative dependence. We show…

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德国与美国失业序列中估计季节与非季节成分的周期相关性AI 解读

The authors examine the orthogonality assumption of seasonal and nonseasonal components for official quarterly unemployment figures in Germany and the United States. Although nonperiodic correlations do not seem to reject the orthogonality assumption, a periodic analysis based on correlation functions that vary with the seasons indicates the violation of orthogonality. The authors find that the unadjusted data can be described by periodic autoregressive models with a unit…

动态渐近理想模型与有限阶逼近AI 解读

The authors extend W. A. Barnett and A. Jonas's (1983) asymptotically ideal model (AIM) to model for the possibility that the data were generated by a dynamic process. Prediction errors for dynamic and static AIM models are compared for various simulated datasets. Monetary data are also used to evaluate the AIM specifications. There is substantial evidence that an AR(1) correction considerably improves the quality of low-order finite approximations of AIM with the cost of…

商业周期特征的度量与比较AI 解读

Since the extensive work by Burns and Mitchell, many economists have interpreted economic fluctuations in terms of business-cycle phases. Given this, the authors argue that, in addition to usual model-selection criteria currently used in the profession, the adequacy of a univariate macroeconomic time series model should be based on its ability to replicate two important business-cycle features of the U.S. data-duration and amplitude. The authors propose several checks for…

季节调整与其他数据变换AI 解读

In this paper, it is shown that the case for using optimal signal extraction filters is not all that convincing once it is recognized that seasonal adjustment is typically not the only transformation applied to data. Seasonal adjustment is viewed as any general linear filter. All other data transformations are also assumed to be linear. While optimal filters always dominate uniform filters, their dominance critically depends on performing seasonal adjustment and the other…

线性协整时间序列系统中的渐近推断AI 解读

This paper considers vector-valued nonstationary time series models, in particular, autoregressive models, whose nonstationarity is driven by a few nonstationary (induced by “unit roots”) trends, in such a way that some of the linear combinations of the components of the vector model will be stationary. Models of this form are called cointegrated models. These stationary linear combinations are called cointegrating relationships. Asymptotic inference problems associated with…

带宽选择、预白化与 Phillips–Perron 检验的功效AI 解读

This study examines several important practical issues concerning nonparametric estimation of the innovation variance for the Phillips-Perron (PP) test. A Monte Carlo study is conducted to evaluate the potential effects of kernel choice, databased bandwidth selection, and prewhitening on the power property of the PP test in finite samples. The Monte Carlo results are instructive. Although the kernel choice is found to make little difference, data-based bandwidth selection…

扩散过程之间的长期共动AI 解读

The aim of this paper is to characterize and analyze long-run comovements among diffusion processes. Broadly speaking, if X = ( X 1 ,, X 2 ,;t ≥ 0) is a nonergodic diffusion in R 2 , but there exists a linear combination, say, γ′ X , that is instead ergodic in R, then we say there exists a linear stochastic comovement between the components of X . Linear diffusions exhibiting stochastic comovements admit an error correction representation. Estimation of γ and hypothesis…

基于自回归近似的 ARMA 模型简便估计与识别技术AI 解读

We examine simple estimators for general ARMA models and a corresponding identification method. Both estimation and identification are based on a matrix formed from the coefficients of an autoregressive approximation to the process of interest. We show that a zero determinant of this matrix is necessary and sufficient for the existence of a common factor in autoregressive and moving average lag polynomials, and therefore for redundant parameters in the model. Simulation…

非高斯观测时间序列的似然分析AI 解读

In this paper we provide methods for estimating non-Gaussian time series models. These techniques rely on Markov chain Monte Carlo to carry out simulation smoothing and Bayesian posterior analysis of parameters, and on importance sampling to estimate the likelihood function for classical inference. The time series structure of the models is used to ensure that our simulation algorithms are efficient.

Monti 的 ARMA 模型适合性综合检验有限样本分布的进一步结果AI 解读

This note investigates the finite-sample performance of Monti's test, paying special attention to its estimated sizes and empirical powers. Our simulation results indicate that (i) the test size can be affected by the choice of the number of residual partial autocorrelations, m, and (ii) the empirical powers of the Monti and the Ljung-Box tests are similar in the cases of both seasonal and nonseasonal data if m is properly chosen.

非高斯状态空间模型的蒙特卡洛最大似然估计AI 解读

State space models are considered for observations which have non-Gaussian distributions. We obtain accurate approximations to the loglikelihood for such models by Monte Carlo simulation. Devices are introduced which improve the accuracy of the approximations and which increase computational efficiency. The loglikelihood function is maximised numerically to obtain estimates of the unknown hyperparameters. Standard errors of the estimates due to simulation are calculated.…

非负贝叶斯时间序列模型的性质与推广AI 解读

Summary We study the most basic Bayesian forecasting model for exponential family time series, the power steady model (PSM) of Smith, in terms of observable properties of one-step forecast distributions and sample paths. The PSM implies a constraint between location and spread of the forecast distribution. Including a scale parameter in the models does not always give an exact solution free of this problem, but it does suggest how to define related models free of the…

带条件异方差的分数积分 ARMA 时间序列模型AI 解读

This article considers fractionally integrated autoregressive moving-average time series models with conditional heteroscedasticity, which combines the popular generalized autoregressive conditional heteroscedastic (GARCH) and the fractional (ARMA) models. The fractional differencing parameter d can be greater than 1/2, thus incorporating the important unit root case. Some sufficient conditions for stationarity, ergodicity, and existence of higher-order moments are derived.…