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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
Modelling structural breaks, long memory and stock market volatility: an overview
Small sample properties of forecasts from autoregressive models under structural breaks
Robust GMM tests for structural breaks
A parametric bootstrap test for cycles
周期性的参数自助检验
The paper proposes a simple test for the hypothesis of strong cycles and as a by-product a test for weak dependence for linear processes. We show that the limit distribution of the test is the maximum of a (semi)Gaussian process G (τ), τ ∈ [0; 1]. Because the covariance structure of G (τ) is a complicated function of τ and model dependent, to obtain the critical values (if possible) of maxτ∈[0;1] G (τ) may be difficult. For this reason we propose a bootstrap scheme in the…
Order selection for same-realization predictions in autoregressive processes
自回归过程中同一实现预测的阶数选择
Assume that observations are generated from an infinite-order autoregressive [AR(∞)] process. Shibata [Ann. Statist. 8 (1980) 147–164] considered the problem of choosing a finite-order AR model, allowing the order to become infinite as the number of observations does in order to obtain a better approximation. He showed that, for the purpose of predicting the future of an independent replicate, Akaike’s information criterion (AIC) and its variants are asymptotically…
High moment partial sum processes of residuals in GARCH models and their applications
GARCH 模型残差的高阶矩部分和过程及其应用
In this paper we construct high moment partial sum processes based on residuals of a GARCH model when the mean is known to be 0. We consider partial sums of kth powers of residuals, CUSUM processes and self-normalized partial sum processes. The kth power partial sum process converges to a Brownian process plus a correction term, where the correction term depends on the kth moment μk of the innovation sequence. If μk=0, then the correction term is 0 and, thus, the kth power…
Cross-validation in nonparametric regression with outliers
含离群值非参数回归中的交叉验证
A popular data-driven method for choosing the bandwidth in standard kernel regression is cross-validation. Even when there are outliers in the data, robust kernel regression can be used to estimate the unknown regression curve [Robust and Nonlinear Time Series Analysis. Lecture Notes in Statist. (1984) 26 163–184]. However, under these circumstances standard cross-validation is no longer a satisfactory bandwidth selector because it is unduly influenced by extreme prediction…
Recursive Monte Carlo filters: Algorithms and theoretical analysis
递归蒙特卡洛滤波:算法与理论分析
Recursive Monte Carlo filters, also called particle filters, are a powerful tool to perform computations in general state space models. We discuss and compare the accept–reject version with the more common sampling importance resampling version of the algorithm. In particular, we show how auxiliary variable methods and stratification can be used in the accept–reject version, and we compare different resampling techniques. In a second part, we show laws of large numbers and a…
Generating schemes for long memory processes: regimes, aggregation and linearity
Size and power of tests of stationarity in highly autocorrelated time series
Sign tests for long-memory time series
Estimation and Testing of Forecast Rationality under Flexible Loss
灵活损失函数下预测理性的估计与检验
In situations where a sequence of forecasts is observed, a common strategy is to examine "rationality" conditional on a given loss function. We examine this from a different perspective—supposing that we have a family of loss functions indexed by unknown shape parameters, then given the forecasts can we back out the loss function parameters consistent with the forecasts being rational even when we do not observe the underlying forecasting model? We establish identification…
Panel Stationarity Tests for Purchasing Power Parity With Cross-Sectional Dependence
允许横截面依赖的购买力平价面板平稳性检验
We investigate the purchasing power parity (PPP) hypothesis for a group of 17 countries using a new panel-based test of stationarity that allows for arbitrary cross-sectional dependence. We treat the short-run time series dynamics nonparametrically and thus avoid the need to fit separate, and potentially misspecified, models for the individual series. The statistic is simple to compute and uses standard normal critical values, even in the presence of a wide range of…
Do Panels Help Solve the Purchasing Power Parity Puzzle?
面板数据有助于解决购买力平价之谜吗?
Although Rogoff described the “remarkable consensus” of 3- to 5-year half-lives of purchasing power parity (PPP) deviations among studies using long-horizon data, recent works using panel methods with post-1973 data report shorter half-lives of 2 to 2.5 years. But these studies do not use appropriate techniques to measure persistence. We extend median-unbiased estimation methods to the panel context, calculate both point estimates and confidence intervals, and provide strong…
An Unobserved-Component Model With Switching Permanent and Transitory Innovations
永久与暂时创新切换的不可观测成分模型
This article proposes an unobserved-component model in which component innovations are governed by a state variable that follows a Markov process. The proposed model is capable of describing both stationary and nonstationary behaviors of real data and allows the random innovations to have permanent and transitory effects in different periods. The model also permits a deterministic trend with or without breaks and hence bridges the gap between the trend-stationary model and a…
Confidence Intervals for Half-Life Deviations From Purchasing Power Parity
购买力平价偏离半衰期的置信区间
Existing point estimates of half-life deviations from purchasing power parity (PPP), around 3–5 years, suggest that the speed of convergence is extremely slow. This article assesses the degree of uncertainty around these point estimates by using local-to-unity asymptotic theory to construct confidence intervals that are robust to high persistence in small samples. The empirical evidence suggests that the lower bound of the confidence interval is between four and eight…
A Test for Superior Predictive Ability
优越预测能力检验
We propose a new test for superior predictive ability. The new test compares favorably to the reality check (RC) for data snooping, because it is more powerful and less sensitive to poor and irrelevant alternatives. The improvements are achieved by two modifications of the RC. We use a studentized test statistic that reduces the influence of erratic forecasts and invoke a sample-dependent null distribution. The advantages of the new test are confirmed by Monte Carlo…
Evaluation and Combination of Conditional Quantile Forecasts
条件分位数预测的评价与组合
We propose an encompassing test for comparing conditional quantile forecasts in an out-of-sample framework. Our test provides a basis for forecast combination when encompassing is rejected. Its central features are (1) use of the “tick” loss function, (2) a conditional approach to out-of-sample evaluation, and (3) derivation in an environment with asymptotically nonvanishing estimation uncertainty. Our approach is valid under general conditions; the forecasts can be based on…
A Trading Approach to Testing for Predictability
检验可预测性的交易策略方法
We propose a market timing test for conditional mean independence of financial returns. The new excess predictability (EP) test statistic has an interpretation of a properly normalized return of a certain trading strategy. We discuss similarities of the EP test to the popular directional accuracy (DA) test of Pesaran and Timmermann. Power properties of the EP test are advantageous, and size properties are comparable to those of the DA test. We illustrate application of the…
Powerful Trend Function Tests That Are Robust to Strong Serial Correlation, With an Application to the Prebisch–Singer Hypothesis
对强序列相关稳健的高功效趋势函数检验:普雷维什—辛格假说的应用
We propose tests for hypotheses on the parameters of the deterministic trend function of a univariate time series. The tests do not require knowledge of the form of serial correlation in the data, and they are robust to strong serial correlation. The data can contain a unit root and still have the correct size asymptotically. The tests that we analyze are standard heteroscedasticity autocorrelation robust tests based on nonparametric kernel variance estimators. We analyze…
A TEST FOR COMPARING MULTIPLE MISSPECIFIED CONDITIONAL INTERVAL MODELS
多个误设条件区间模型的比较检验
This paper introduces a test for the comparison of multiple misspecified conditional interval models, for the case of dependent observations. Model accuracy is measured using a distributional analog of mean square error, in which the approximation error associated with a given model, say, model i, for a given interval, is measured by the expected squared difference between the conditional confidence interval under model i and the “true” one.When comparing more than two…
ASYMPTOTICS OF THE QMLE FOR A CLASS OF ARCH(q) MODELS
一类 ARCH(q) 模型准极大似然估计的渐近性质
Strong consistency and asymptotic normality are established for the quasi-maximum likelihood estimator for a class of ARCH(q) models. The conditions are that the ARCH process is geometrically ergodic with a moment of arbitrarily small order. Furthermore for consistency, we assume that the second-order moment exists for the nondegenerate rescaled errors and, similarly, that the fourth-order moment exists for asymptotic normality to hold. Contrary to existing literature on…
LIMITED TIME SERIES WITH A UNIT ROOT
取值范围受限的单位根时间序列
This paper develops an asymptotic theory for integrated and near-integrated time series whose range is constrained in some ways. Such a framework arises when integration and cointegration analyses are applied to time series that are bounded either by construction or because they are subject to control. The asymptotic properties of some commonly used integration tests are discussed; the bounded unit root distribution is introduced to describe the limiting distribution of the…