Maximum Likelihood Estimation of the Fractional Differencing Parameter in an Arfima Model Using Wavelets
In this paper, we examine the finite-sample properties of the approximate maximum likelihood estimate (MLE) of the fractional differencing parameter d in an ARFIMA(p, d, q) model based on the wavelet coefficients. Ignoring wavelet coefficients of higher order of resolution, the remaining wavelet coe...
محفوظ في:
| المؤلفون الرئيسيون: | , , |
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| التنسيق: | text |
| اللغة: | English |
| منشور في: |
Institutional Knowledge at Singapore Management University
2002
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://ink.library.smu.edu.sg/soe_research/321 |
| الوسوم: |
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| الملخص: | In this paper, we examine the finite-sample properties of the approximate maximum likelihood estimate (MLE) of the fractional differencing parameter d in an ARFIMA(p, d, q) model based on the wavelet coefficients. Ignoring wavelet coefficients of higher order of resolution, the remaining wavelet coefficients approximate a sample of independently and identically distributed normal variates with homogeneous variance within each level. The approximate MLE performs satisfactorily and provides a robust estimate for which the short memory component need not be specified. |
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