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Econometric Approach Of Heteroskedasticity On Financial Time Series In A General Framework

Author

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  • FELICIA RAMONA BIRAU

    (UNIVERSITY OF CRAIOVA,FACULTY OF ECONOMICS AND BUSINESS ADMINISTRATION)

Abstract

The 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.

Suggested Citation

  • Felicia Ramona Birau, 2012. "Econometric Approach Of Heteroskedasticity On Financial Time Series In A General Framework," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 4, pages 74-77, December.
  • Handle: RePEc:cbu:jrnlec:y:2012:v:4i:p:74-77
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    References listed on IDEAS

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    1. Bollerslev, Tim & Engle, Robert F, 1993. "Common Persistence in Conditional Variances," Econometrica, Econometric Society, vol. 61(1), pages 167-186, January.
    2. Strozzi, Fernanda & Zaldı́var, José-Manuel & Zbilut, Joseph P, 2002. "Application of nonlinear time series analysis techniques to high-frequency currency exchange data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(3), pages 520-538.
    3. Guneratne Banda Wickremasinghe, 2004. "Efficiency Of Foreign Exchange Markets: A Developing Country Perspective," International Finance 0406004, EconWPA.
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