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Fitting nonlinear time‐series models with applications to stochastic variance models
Author(s) -
Shephard N.
Publication year - 1993
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.3950080509
Subject(s) - series (stratigraphy) , variance (accounting) , nonlinear system , computer science , estimation , maximum likelihood , stochastic modelling , time series , estimation theory , mathematical optimization , econometrics , mathematics , algorithm , statistics , machine learning , economics , paleontology , physics , accounting , quantum mechanics , management , biology
New strategies for the implementation of maximum likelihood estimation of nonlinear time series models are suggested. They make use of recent work on the EM algorithm and iterative simulation techniques. The estimation procedures are applied to the problem of fitting stochastic variance models to exchange rate data.