We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Adaptive pointwise estimation in time-inhomogeneous conditional heteroscedasticity models.
- Authors
ČÍŽEK, P.; HÄRDLE, W.; SPOKOINY, V.
- 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.
- Subjects
HETEROSCEDASTICITY; ANALYSIS of variance; LEAST squares; ECONOMETRICS; MONTE Carlo method
- Publication
Econometrics Journal, 2009, Vol 12, Issue 2, p248
- ISSN
1368-4221
- Publication type
Article
- DOI
10.1111/j.1368-423X.2009.00292.x