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Let's get LADE: robust estimation of semiparametric multiplicative volatility models

Authors: Bonsoo Koo and Oliver Linton
Date: 31 August 2015
Type: Journal Article, Econometric Theory, Vol. 31, No. 4, pp. 671--702
DOI: 10.1017/S0266466614000516

Abstract

We investigate a model in which we connect slowly time varying unconditional long-run volatility with short-run conditional volatility whose representation is given as a semi-strong GARCH(1,1) process with heavy tailed errors. We focus on robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility is totally unspecified whereas the short-run conditional volatility is a parametric semi-strong GARCH(1,1) process. We propose different robust estimation methods for nonstationary and strictly stationary GARCH parameters with nonparametric long-run volatility function. Our estimation is based on a two-step LAD procedure. We establish the relevant asymptotic theory of the proposed estimators. Numerical results lend support to our theoretical results.

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Bonsoo Koo and Oliver Linton March 2013, Let's get LADE: robust estimation of semiparametric multiplicative volatility models, cemmap Working Paper, CWP11/13, Institute for Fiscal Studies

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