论文检索

摘要暂缺

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…

线性回归的自助法标准误估计AI 解读

Standard errors of parameter estimates are widely used in empirical work. The bootstrap often can provide a convenient means of estimating standard errors. The conditions under which bootstrap standard error estimates are theoretically justified have not received much attention, however. This article establishes conditions for the consistency of the moving blocks bootstrap estimators of the variance of the least squares estimator in linear dynamic models with dependent data.…

序列依赖非参数熵度量的渐近分布理论AI 解读

Entropy is a classical statistical concept with appealing properties. Establishing asymptotic distribution theory for smoothed nonparametric entropy measures of dependence has so far proved challenging. In this paper, we develop an asymptotic theory for a class of kernel-based smoothed nonparametric entropy measures of serial dependence in a time-series context. We use this theory to derive the limiting distribution of Granger and Lin's (1994) normalized entropy measure of…

互补自动建模方法的比较：RETINA 与 PcGetsAI 解读

In Perez-Amaral, Gallo, and White (2003, Oxford Bulletin of Economics and Statstics 65, 821–838), the authors proposed an automatic predictive modeling tool called relevant transformation of the inputs network approach (RETINA). It is designed to embody flexibility (using nonlinear transformations of the predictors of interest), selective search within the range of possible models, control of collinearity, out-of-sample forecasting ability, and computational simplicity. In…

摘要暂缺

摘要暂缺

依赖异质阵列样本均值的自助法AI 解读

Presently, conditions ensuring the validity of bootstrap methods for the sample mean of (possibly heterogeneous) near epoch dependent (NED) functions of mixing processes are unknown. Here we establish the validity of the bootstrap in this context, extending the applicability of bootstrap methods to a class of processes broadly relevant for applications in economics and finance. Our results apply to two block bootstrap methods: the moving blocks bootstrap of Künsch (1989,…

摘要暂缺

We explore the extension of James–Stein–type estimators in a direction that enables them to preserve their superiority when the sample size goes to infinity. Instead of shrinking a base estimator toward a fixed point, we shrink it toward a data-dependent point. We provide an analytic expression for the asymptotic risk and bias of James–Stein–type estimators shrunk toward a data-dependent point and prove that they have smaller asymptotic risk than the base estimator.…

数据窥探的现实检验AI 解读

Data snooping occurs when a given set of data is used more than once for purposes of inference or model selection. When such data reuse occurs, there is always the possibility that any satisfactory results obtained may simply be due to chance rather than to any merit inherent in the method yielding the results. This problem is practically unavoidable in the analysis of time-series data, as typically only a single history measuring a given phenomenon of interest is available…

摘要暂缺

摘要暂缺

In this paper we utilize White's Reality Check bootstrap methodology (White (1999)) to evaluate simple technical trading rules while quantifying the data‐snooping bias and fully adjusting for its effect in the context of the full universe from which the trading rules were drawn. Hence, for the first time, the paper presents a comprehensive test of performance across all technical trading rules examined. We consider the study of Brock, Lakonishok, and LeBaron (1992), expand…

仅在备择下存在干扰参数的一致设定检验AI 解读

The nonparametric and the nuisance parameter approaches to consistently testing statistical models are both attempts to estimate topological measures of distance between a parametric and a nonparametric fit, and neither dominates in experiments. This topological unification allows us to greatly extend the nuisance parameter approach. How and why the nuisance parameter approach works and how it can be extended bear closely on recent developments in artificial neural networks.…

高崩溃点条件离散度估计：应用于标普500日收益波动率AI 解读

The authors show that quasimaximum likelihood (QML) estimators for conditional dispersion models can be severely affected by a small number of outliers such as market crashes and rallies, and they propose new estimation strategies (the two-stage Hampel estimators and two-stage S-estimators) resistant to the effects of outliers and study the properties of these estimators. They apply their methods to estimate models of the conditional volatility of the daily returns of the…

Hilbert 空间值依赖异质数组的中心极限定理与函数中心极限定理及应用AI 解读

We obtain new central limit theorems (CLT's) and functional central limit theorems (FCLT's) for Hilbert-valued arrays near epoch dependent on mixing processes, and also new FCLT's for general Hilbert-valued adapted dependent heterogeneous arrays. These theorems are useful in delivering asymptotic distributions for parametric and nonparametric estimators and their functionals in time series econometrics. We give three significant applications for near epoch dependent…

摘要暂缺

结构变化的实时监测AI 解读

Contemporary tests for structural change are designed to detect a structural break within a given historical data set of fixed size. Due to the law of the iterated logarithm, these one-shot tests cannot be applied to monitor out-of-sample stability each time new data arrive. The authors propose and analyze two real-time monitoring procedures with controlled size asymptotically: the fluctuation and CUSUM monitoring procedures. Simulation results show that the proposed…

Hilbert 空间值 mixingale 的大数定律及其应用AI 解读

To obtain consistency results for nonparametric estimators based on stochastic processes relevant in econometrics, we introduce the notions of Hilbert space-valued L p mixingales and near-epoch dependent arrays, and we prove weak and strong laws of large numbers by using a new exponential inequality for Hilbert ( H ) space-valued martingale difference arrays. We follow Andrews (1988, Econometric Theory 4, 458–467), Hansen (1991, Econometric Theory 7, 213–221; 1992,…

摘要暂缺

有限样本崩溃点的替代定义及其回归估计应用AI 解读

We propose an alternative definition of the finite-sample breakdown point. This breakdown point is invariant with respect to reparameterization and compatible with the Donoho-Huber breakdown point in linear regression situations. It also overcomes certain limitations of the definition proposed by Stromberg and Ruppert and can be used in a wide range of estimation problems. We investigate the breakdown properties of some nonlinear regression estimators. These results alert us…

摘要暂缺

通过非参数级数回归进行一致的模型设定检验AI 解读

This paper proposes two consistent one-sided specification tests for parametric regression models, one based on the sample covariance between the residual from the parametric model and the discrepancy between the parametric and nonparametric fitted values; the other based on the difference in sums of squared residuals between the parametric and nonparametric models. The authors estimate the nonparametric model by series regression. The new test statistics converge in…