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Threshold Detection in Autoregressive Non-linear Models

Järås, Jacob LU and Mohammadipour Gishani, Azadeh LU (2010) STAM01 20101
Department of Statistics
Abstract
In this paper we fit non-linear models. We build Threshold Autoregressive (TAR) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models and estimate the parameters associated to the models, e.g. the threshold for the TAR model. The TAR and the GARCH model concept are applied to simulated data and to three empirical datasets, two River flow time series and one Blowfly data set. We observe significant non-linear effects from the tests for the three empirical time series. Two different TAR models fit to the Blowfly data. We fit ultimately TAR models to the river data sets. The fitted AR-GARCH model does not give satisfactory results for the three empirical data sets.
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author
Järås, Jacob LU and Mohammadipour Gishani, Azadeh LU
supervisor
organization
course
STAM01 20101
year
type
H1 - Master's Degree (One Year)
subject
keywords
Threshold Autoregressive Model, Non-linear Time Series, GARCH., ARCH
language
English
id
1636260
date added to LUP
2010-08-26 12:43:27
date last changed
2010-08-26 12:43:27
@misc{1636260,
  abstract     = {In this paper we fit non-linear models. We build Threshold Autoregressive (TAR) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models and estimate the parameters associated to the models, e.g. the threshold for the TAR model. The TAR and the GARCH model concept are applied to simulated data and to three empirical datasets, two River flow time series and one Blowfly data set. We observe significant non-linear effects from the tests for the three empirical time series. Two different TAR models fit to the Blowfly data. We fit ultimately TAR models to the river data sets. The fitted AR-GARCH model does not give satisfactory results for the three empirical data sets.},
  author       = {Järås, Jacob and Mohammadipour Gishani, Azadeh},
  keyword      = {Threshold Autoregressive Model,Non-linear Time Series,GARCH.,ARCH},
  language     = {eng},
  note         = {Student Paper},
  title        = {Threshold Detection in Autoregressive Non-linear Models},
  year         = {2010},
}