Abstract
A Bartlett-type formula is proposed for the asymptotic distribution of the sample autocorrelations of nonlinear processes. The asymptotic covariances between sample autocorrelations are expressed as the sum of two terms. The first term corresponds to the standard Bartlett's formula for linear processes, involving only the autocorrelation function of the observed process. The second term, which is specific to nonlinear processes, involves the autocorrelation function of the observed process, the kurtosis of the linear innovation process and the autocorrelation function of its square. This formula is obtained under a symmetry assumption on the linear innovation process. It is illustrated on ARMA-GARCH models and compared to the standard formula. An empirical application on financial time series is proposed.
| Original language | English |
|---|---|
| Pages (from-to) | 449-465 |
| Number of pages | 17 |
| Journal | Journal of Time Series Analysis |
| Volume | 30 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Jul 2009 |
| Externally published | Yes |
Keywords
- Bartlett's formula
- GARCH model
- Nonlinear time series model
- Sample autocorrelation
- Weak white noise