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SIMULATION AND ESTIMATION OF LONG MEMORY CONTINUOUS TIME MODELS
Author(s) -
Comte F.
Publication year - 1996
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.1996.tb00262.x
Subject(s) - autoregressive model , mathematics , monte carlo method , estimation , long memory , autoregressive–moving average model , filter (signal processing) , sample (material) , discrete time and continuous time , algorithm , econometrics , statistics , computer science , volatility (finance) , chemistry , management , chromatography , computer vision , economics
. Some general properties of long memory continuous time processes are recalled or proved. Methods of simulation are studied. A comparison with the usual discrete time autoregressive fractionally integrated moving‐average filter is made and illustrations are provided. Then, two methods of estimation of the parameters of such a model from a discrete sample are studied, both theoretically and empirically, with Monte Carlo experiments.