 Adaptive pointwise estimation in time-inhomogeneous conditional heteroscedasticity modelsP. Čížek, Wolfgang Härdle and V. Spokoiny Econometrics Journal, 2009, vol. 12, issue 2, 248-271 Abstract: This paper offers a new method for estimation and forecasting of the volatility of financial time series when the stationarity assumption is violated. Our general, local parametric approach particularly applies to general varying-coefficient parametric models, such as GARCH, whose coefficients may arbitrarily vary with time. Global parametric, smooth transition and change-point models are special cases. The method is based on an adaptive pointwise selection of the largest interval of homogeneity with a given right-end point by a local change-point analysis. We construct locally adaptive estimates that can perform this task and investigate them both from the theoretical point of view and by Monte Carlo simulations. In the particular case of GARCH estimation, the proposed method is applied to stock-index series and is shown to outperform the standard parametric GARCH model. Copyright © 2009 The Author(s). Journal compilation © Royal Economic Society 2009 Date: 2009 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ect:emjrnl:v:12:y:2009:i:2:p:248-271 Ordering information: This journal article can be ordered from Access Statistics for this article Econometrics Journal is currently edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jaap Abbring and Marius Ooms More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC. |
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