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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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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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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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Estimation of the long-memory stochastic volatility model parameters that is robust to level shifts and deterministic trends
McCloskey, Adam - 2012 - This version: October 2012
parametric short-memory models, can be used to estimate the long-memory stochastic volatility model parameters in the presence of …-memory. -- stochastic volatility ; frequency domain estimation ; robust estimation ; spurious persistence ; long-memory ; level shifts …
Persistent link: https://www.econbiz.de/10009660446
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Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility
Jensen, Mark J. - 2015
Empirical volatility studies have discovered nonstationary, long-memory dynamics in the volatility of the stock market … found with nonparametric estimates of the fractional differencing parameter d, for financial volatility. In this paper, a …, stochastic volatility (SV-FIAR) model. Joint estimates of the autoregressive and fractional differencing parameters of volatility …
Persistent link: https://www.econbiz.de/10011382237
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Spot variance path estimation and its application to high frequency jump testing
Bos, Charles S.; Janus, Paweł; Koopman, Siem Jan - 2009
This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used...
Persistent link: https://www.econbiz.de/10011379469
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A general double robustness result for estimating average treatment effects
Słoczyński, Tymon; Wooldridge, Jeffrey M. - 2014
In this paper we study doubly robust estimators of various average treatment effects under unconfoundedness. We unify and extend much of the recent literature by providing a very general identification result which covers binary and multi-valued treatments; unnormalized and normalized weighting;...
Persistent link: https://www.econbiz.de/10010339580
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Semiparametric estimation and inference using doubly robust moment conditions
Rothe, Christoph; Firpo, Sérgio Pinheiro - 2013
We study semiparametric two-step estimators which have the same structure as parametric doubly robust estimators in their second step, but retain a fully nonparametric specification in the first step. Such estimators exist in many economic applications, including a wide range of missing data and...
Persistent link: https://www.econbiz.de/10009792511