Semiparametric Estimation of the Intensity of Long Memory in Conditional Heteroskedasticity
- Cite this article as:
- Giraitis, L., Kokoszka, P., Leipus, R. et al. Statistical Inference for Stochastic Processes (2000) 3: 113. doi:10.1023/A:1009951213271
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The paper is concerned with the estimation of the long memory parameter in a conditionally heteroskedastic model proposed by Giraitis et al. (1999b). We consider estimation methods based on the partial sums of the squared observations, which are similar in spirit to the classical R / S analysis, as well as spectral domain approximate maximum likelihood estimators. We review relevant theoretical results and present an empirical simulation study.