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    Investigating some estimators of the fractional degree of differencing, in long memory time series

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    Date
    2011-05
    Author
    Kiogou, Sebastien Dalli
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    Abstract
    We investigated three estimators of the fractional parameter d, in long memory time series. Discussed in [4], the rst estimator is based on a regression analysis using the periodogram of the long memory series; the second estimator which is discussed in [11, 10], is based on a regression analysis using a lag-window spectral density estimator; the third estimator performs a maximum likelihood estimation (MLE) of d using the fast and accurate method of [8]. To conduct our investigation, we generated synthetic ARFIMA(p; d; q) samples where d = :25 and d = :45. Computational results showed that in general the MLE method performs better in large samples whereas the [4] proposed estimator performs better in small samples. Yet, the estimator in [11, 10] behaves better than that proposed by [4] in large samples. While the MLE has the smallest standard errors in both small and large samples, the standard errors of the [4] approach are the largest.
    URI
    http://purl.galileo.usg.edu/uga_etd/kiogou_sebastien_d_201105_ms
    http://hdl.handle.net/10724/27190
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