A unified approach to standardized‐residuals‐based correlation tests for GARCH‐type models
提出一种统一方法，用于基于标准化残差的相关检验来诊断GARCH型模型，该方法能处理估计不确定性、适用于多种误差分布，并提出了幂变换序列相关检验，在金融时间序列分析中优于现有检验。
Abstract In this paper, we propose a unified approach to generating standardized‐residuals‐based correlation tests for checking GARCH‐type models. This approach is valid in the presence of estimation uncertainty, is robust to various standardized error distributions, and is applicable to testing various types of misspecifications. By using this approach, we also propose a class of power‐transformed‐series (PTS) correlation tests that provides certain robustifications and power extensions to the Box–Pierce, McLeod–Li, Li–Mak, and Berkes–Horváth–Kokoszka tests in diagnosing GARCH‐type models. Our simulation and empirical example show that the PTS correlation tests outperform these existing autocorrelation tests in financial time series analysis. Copyright © 2008 John Wiley & Sons, Ltd.