Econometric Approach Of Heteroskedasticity On Financial Time Series In A General Framework
AbstractThe aim of this paper is to provide an overview of the diagnostic tests for detecting heteroskedasticity on financial time series. In financial econometrics, heteroskedasticity is generally associated with cross sectional data but can also be identified modeling time series data. The presence of heteroscedasticity in financial time series can be caused by certain specific factors, like a model misspecification, inadequate data transformation or as a result of certain outliers. Heteroskedasticity arise when the homoskedasticity assumption is violated. Testing for the presence of heteroskedasticity in financial time is performed by applying diagnostic test, such as : Breusch-Pagan LM test, White’s test, Glesjer LM test, Harvey-Godfrey LM test, Park LM test and Goldfeld-Quand test.
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Bibliographic InfoArticle provided by Constantin Brancusi University, Faculty of Economics in its journal Constatin Brancusi University of Targu Jiu Annals - Economy Series.
Volume (Year): 4I (2012)
Issue (Month): (December)
heteroskedasticity; linear dependence; variance; volatility clustering; non-normal distribution;
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