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异方差时间序列模型的渐近分布无关诊断检验AI 解读

This article investigates model checks for a class of possibly nonlinear heteroskedastic time series models, including but not restricted to ARMA-GARCH models. We propose omnibus tests based on functionals of certain weighted standardized residual empirical processes. The new tests are asymptotically distribution-free, suitable when the conditioning set is infinite-dimensional, and consistent against a class of Pitman’s local alternatives converging at the parametric rate n…

考虑估计风险的参数化风险价值回测AI 解读

One of the implications of the creation of the Basel Committee on Banking Supervision was the implementation of Value-at-Risk (VaR) as the standard tool for measuring market risk. Since then, the capital requirements of commercial banks with trading activities are based on VaR estimates. Therefore, appropriately constructed tests for assessing the out-of-sample forecast accuracy of the VaR model (backtesting procedures) have become of crucial practical importance. In this…

序列相关的自动 Portmanteau 检验AI 解读

This article introduces a data-driven Box-Pierce test for serial correlation. The proposed test is very attractive compared to the existing ones. In particular, implementation of this test is extremely simple for two reasons: first, the researcher does not need to specify the order of the autocorrelation tested, since the test automatically chooses this number; second, its asymptotic null distribution is chi-square with one degree of freedom, so there is no need of using a…

综合设定检验局部功效不足的问题AI 解读

Designed to have power against all alternatives, omnibus consistent tests are the primary econometric tools for testing the correct specification of parametric conditional means when there is no information about the possible alternative. The main purpose of this paper is to show that, contrary to what is generally believed, omnibus specification tests only have substantial local power against alternatives in a finite-dimensional space (usually unknown to the researcher). We…

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利用投影的回归模型一致诊断检验AI 解读

This paper proposes a consistent test for the goodness-of-fit of parametric regression models that overcomes two important problems of the existing tests, namely, the poor empirical power and size performance of the tests due to the curse of dimensionality and the subjective choice of parameters such as bandwidths, kernels, and integrating measures. We overcome these problems by using a residual marked empirical process based on projections (RMPP). We study the asymptotic…

鞅差假设的广义谱检验AI 解读

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…

线性与非线性时间序列模型的拟合优度检验AI 解读

In this article we study a general class of goodness-of-fit tests for a parametric conditional mean of a linear or nonlinear time series model. Among the properties of the proposed tests are that they are suitable when the conditioning set is infinite-dimensional; that they are consistent against a broad class of alternatives, including Pitman's local alternatives converging at the parametric rate n−1/2, with n the sample size; and that they do not need to choose a lag order…