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WHY FARIMA MODELS ARE BRITTLE
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DOI：10.1142/S0218348X13500126.png)
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Abstract
En 中文
The FARIMA models, which have long-range-dependence (LRD), are widely used in many areas. Through the derivation of a precise characterization of the spectrum and variance time function, we show that this family is very atypical among LRD processes, being extremely close to the fractional Gaussian noise in a precise sense which results in ultra-fast convergence to fGn under rescaling. Furthermore, we show that this closeness property is not robust to additive noise. We argue that the use of FARIMA, and more generally fractionally differenced time series, should be reassessed in some contexts, in particular when convergence rate under rescaling is important and noise is expected.
Keywords:
FARIMA
Fractionally Differenced Process
Self-Similarity
fGn
Long-Range Dependence
Hurst Parameter
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