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Contribution Details
| Type | Conference Presentation |
| Scope | Contributions to practice |
| Title | Unit root and cointegration tests with wavelets |
| Organization Unit | |
| Authors |
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| Presentation Type | speech |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Event Title | Financial Econometrics Conference CIREQ |
| Event Type | conference |
| Event Location | Montreal |
| Event Start Date | May 5 - 2006 |
| Event End Date | May 6 - 2006 |
| Abstract Text | This paper develops a wavelet (spectral) approach to testing the presence of a unit root in a stochastic process. The wavelet approach is appealing, since it is based directly on the different behavior of the spectra of a unit root process and that of a short memory stationary process. By decomposing the variance (energy) of the underlying process into the variance (energy) of its low frequency components and that of its high frequency components via the discrete wavelet transformation (DWT), we design unit root tests which have substantial power against near unit root alternatives. Since DWT is an energy preserving transformation and able to disbalance energy across high and low frequency components of a series, it is possible to isolate the most persistent component of a series in a small number of scaling coefficients. Our tests utilize the wavelet coefficients of the coarsest scale. We generalize our unit root tests to residual based tests for cointegration and to the maximum overlap DWT (MODWT), demonstrate their size and power properties through Monte Carlo simulations, and apply them to financial time series. |
| Other Identification Number | http://www.cirano.qc.ca/realisations/grandes_conferences/methodes_econometriques/FanGencayURoot.pdf |
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