2012/12/11 by Valentin Patilea, Patilea, Valentin, Hamdi Raïssi +1
Economics, Econometrics and Finance · Mathematics · #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #Financial Risk and Volatility Modeling #Market Dynamics and Volatility #Methodology (stat.ME) #stat.ME
paper · pdf · doi:10.48550/arxiv.1212.2652
arxiv created 2012/12/11 · openalex publication_date 2012/12/11 · arxiv updated 2012/12/13 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
The volatility modeling for autoregressive univariate time series is considered. A benchmark approach is the stationary ARCH model of Engle (1982). Motivated by real data evidence, processes with non constant unconditional variance and ARCH effects have been recently introduced. We take into account such possible non stationarity and propose simple testing procedures for ARCH effects. Adaptive McLeod and Li's portmanteau and ARCH-LM tests for checking for second order dynamics are provided. The standard versions of these tests, commonly used by practitioners, suppose constant unconditional variance. We prove the failure of these standard tests with time-varying unconditional variance. The theoretical results are illustrated by mean of simulated and real data.