A CENTRAL LIMIT THEOREM OF FOURIER TRANSFORMS OF STRONGLY DEPENDENT STATIONARY PROCESSES

Yoshihiro Yajima

Journal of Time Series Analysis, 1989, vol. 10, issue 4, 375-383

Abstract: Abstract. We consider a limiting distribution of the finite Fourier transforms of observations drawn from a strongly dependent stationary process. It is proved that the finite Fourier transforms at different frequencies are asymptotically independent and normally distributed. Our result can apply to a fractional autoregressive integrated moving‐average process and a fractional Gaussian noise, two examples of strongly dependent stationary processes.

Date: 1989
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jtsera:v:10:y:1989:i:4:p:375-383

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