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Time Dependence and Moments of a Family of Time‐Varying Parameter Garch in Mean Models
Author(s) -
Arvanitis Stelios,
Demos Antonis
Publication year - 2004
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 - 10.1046/j.0143-9782.2003.01771.x
Subject(s) - heteroscedasticity , stylized fact , mathematics , autoregressive conditional heteroskedasticity , series (stratigraphy) , econometrics , identification (biology) , method of moments (probability theory) , statistical physics , moment (physics) , statistics , economics , volatility (finance) , estimator , paleontology , botany , physics , biology , macroeconomics , classical mechanics
. In this paper we consider the time series dependence, stationarity, and higher moments issues of a family of first‐order conditionally heteroskedastic in mean models with a possibly time‐varying mean parameter. The interest in these models lies in the fact that economic theory and physics often require the connection between the first and second conditional moments of time series. Our results reveal important properties of these models, which are consistent with stylized facts in financial and turbulence data sets. They can also be employed for model identification, estimation, and testing.