Bootstrapping nonparametric estimators of the volatility function

We prove that the bootstrap works in a quite general sense for nonparametric estimators of the trend and volatility functions in nonlinear AR-ARCH-models. We illustrate the implications of this result by constructing uniform confidence bands for those functions based on localized nonparametric funct...

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Published in:Journal of econometrics 2004, Vol.118 (1), p.189-218
Main Authors: Franke, Jürgen, Neumann, Michael H., Stockis, Jean-Pierre
Format: Article
Language:English
Subjects:
ARCH process
Bootstrap
Confidence band
Econometric models
Econometrics
Economic methodology
Economic models
Economic theory
Estimation
Mathematical economics
Nonparametric estimates
Rates of return
Studies
Time series
Volatility
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description We prove that the bootstrap works in a quite general sense for nonparametric estimators of the trend and volatility functions in nonlinear AR-ARCH-models. We illustrate the implications of this result by constructing uniform confidence bands for those functions based on localized nonparametric function estimates. As an application, we study the trend and volatility of a time series of high frequency foreign exchange rate returns.
doi_str_mv 10.1016/S0304-4076(03)00140-4
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source International Bibliography of the Social Sciences (IBSS); Backfile Package - Economics, Econometrics and Finance (Legacy) [YET]; ScienceDirect Journals; Backfile Package - Mathematics (Legacy) [YMT]
subjects ARCH process
Bootstrap
Confidence band
Econometric models
Econometrics
Economic methodology
Economic models
Economic theory
Estimation
Mathematical economics
Nonparametric estimates
Rates of return
Studies
Time series
Volatility
title Bootstrapping nonparametric estimators of the volatility function
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