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Let's Get Lade : Robust Estimation of Semiparametric Multiplicative Volatility Models
Linton, Oliver B. - 2013
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 …
Persistent link: https://www.econbiz.de/10013084890
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EmmPack 1.01 : C/C++ code for use with Ox for estimation of univariate stochastic volatility models with the efficient method of moments
Sluis, Pieter J. van der - 1998
the Efficient Method of Moments implemented to estimatestochastic volatility models this will surely be the case … method of momentstechnique for a broad range of univariate stochastic volatility models. As a side effect of the … volatility models. It describes the program. Some examples are given from other workof the author. Technicalities are given in …
Persistent link: https://www.econbiz.de/10010533201
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Let's get LADE : robust estimation of semiparametric multiplicative volatility models
Koo, Bonsoo; Linton, Oliver - 2013
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 …
Persistent link: https://www.econbiz.de/10009719116
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Efficient Semi-Parametric Estimation of Non-Gaussian GARCH Processes
Godin, Frédéric - 2016
Semi-parametric estimators for non-Gaussian GARCH processes based on Feasible Weighted Least Squares (FWLS) are proposed. The estimators are consistent and do not require the specification of the innovations distribution family. The FWLS estimators incorporate information related to the skewness...
Persistent link: https://www.econbiz.de/10012978175
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Tilted Nonparametric Estimation of Volatility Functions with Empirical Applications
Phillips, Peter C. B.; Xu, Ke-Li - 2010
the total volatility function in a continuous-time jump diffusion model …
Persistent link: https://www.econbiz.de/10014049786
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Locally robust semiparametric estimation
Chernozhukov, Victor; Escanciano, Juan Carlos; … - 2016
This paper shows how to construct locally robust semiparametric GMM estimators, meaning equivalently moment conditions have zero derivative with respect to the first step and the first step does not affect the asymptotic variance. They are constructed by adding to the moment functions the...
Persistent link: https://www.econbiz.de/10011517194
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Locally robust semiparametric estimation
Chernozhukov, Victor; Escanciano, Juan Carlos; … - 2018
We give a general construction of debiased/locally robust/orthogonal (LR) moment functions for GMM, where the derivative with respect to first step nonparametric estimation is zero and equivalently first step estimation has no effect on the influence function. This construction consists of...
Persistent link: https://www.econbiz.de/10011824067
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Smoothed influence function : another view at robust nonparametric regression
Tamine, Julien - 2001
In this work, we introduce a smoothed influence function that constitute a theoretical tool for studying the outliers robustness properties of a large class of nonparametric estimators. With this tool, we first show the nonrobustness of the Nadaraya-Watson estimator of regression. Then we show...
Persistent link: https://www.econbiz.de/10009626684
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Finite-Sample Generalized Confidence Distributions and Sign-Based Robust Estimators In Median Regressions with Heterogeneous Dependent Errors
Coudin, Elise - 2017
We study the problem of estimating the parameters of a linear median regression without any assumption on the shape of the error distribution -- including no condition on the existence of moments -- allowing for heterogeneity (or heteroskedasticity) of unknown form, noncontinuous distributions,...
Persistent link: https://www.econbiz.de/10012962776
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Semiparametric Robust Estimation of Truncated and Censored Regression Models
Cizek, Pavel - 2008
Many estimation methods of truncated and censored regression models such as the maximum likelihood and symmetrically censored least squares (SCLS) are sensitive to outliers and data contamination as we document. Therefore, we propose a semiparametric general trimmed estimator (GTE) of truncated...
Persistent link: https://www.econbiz.de/10014047660