The generalised autocovariance function is defined for a stationary stochastic process as the inverse Fourier transform of the power transformation of the spectral density function. Depending on the value of the transformation parameter, this function nests the inverse and the traditional autocovariance func- tions. A frequency domain non-parametric estimator based on the power transformation of the pooled pe- riodogram is considered and its asymptotic distribution is derived. The results are employed to construct classes of tests of the white noise hypothesis, for clustering and discrimination of stochastic processes and to introduce a novel feature matching estimator of the spectrum.
Tommaso Proietti, Alessandra Luati (2015). The generalised autocovariance function. JOURNAL OF ECONOMETRICS, 186(1), 245-257 [10.1016/j.jeconom.2014.07.004].
The generalised autocovariance function
LUATI, ALESSANDRA
2015
Abstract
The generalised autocovariance function is defined for a stationary stochastic process as the inverse Fourier transform of the power transformation of the spectral density function. Depending on the value of the transformation parameter, this function nests the inverse and the traditional autocovariance func- tions. A frequency domain non-parametric estimator based on the power transformation of the pooled pe- riodogram is considered and its asymptotic distribution is derived. The results are employed to construct classes of tests of the white noise hypothesis, for clustering and discrimination of stochastic processes and to introduce a novel feature matching estimator of the spectrum.| File | Dimensione | Formato | |
|---|---|---|---|
|
ProiettiT_jeconom_2015_postprint.pdf
Open Access dal 05/08/2016
Tipo:
Postprint / Author's Accepted Manuscript (AAM) - versione accettata per la pubblicazione dopo la peer-review
Licenza:
Licenza per Accesso Aperto. Creative Commons Attribuzione - Non commerciale - Non opere derivate (CCBYNCND)
Dimensione
868 kB
Formato
Adobe PDF
|
868 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


