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Nonparametric estimation of a periodic sequence in the presence of a smooth trend

Vogt, Michael; Linton, Oliver - 2012

In this paper, we study a nonparametric regression model including a periodic component, a smooth trend function, and a stochastic error term. We propose a procedure to estimate the unknown period and the function values of the periodic component as well as the nonparametric trend function. The...

Persistent link: https://www.econbiz.de/10009614392

Estimation of stochastic volatility models by nonparametric filtering

Kanaya, Shin; Kristensen, Dennis - 2015

A two-step estimation method of stochastic volatility models is proposed. In the first step, we nonparametrically … estimate the (unobserved) instantaneous volatility process. In the second step, standard estimation methods for fully observed … estimation strategy is applicable to both parametric and nonparametric stochastic volatility models, and can handle both jumps …

Persistent link: https://www.econbiz.de/10010487528

Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction

Cheng, Tingting; Gao, Jiti; Linton, Oliver - 2018

nonstationary. We also establish the estimation theory and asymptotic properties for these models in the short horizon and long …

Persistent link: https://www.econbiz.de/10011775136

Perceived shocks and impulse responses

Giacomini, Raffaella; Lu, Jason; Smetanina, Katja - 2024

This paper develops a novel approach that leverages the information contained in expectations datasets to derive empirical measures of beliefs regarding economic shocks and their dynamic effects. Utilizing a panel of expectation revisions for a single variable across multiple horizons, we...

Persistent link: https://www.econbiz.de/10015123512

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

Koo, Bonsoo; Linton, Oliver - 2013

run volatility function. Our estimation is based on a two-step LAD procedure. We establish the relevant asymptotic theory … robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility … propose different robust estimation methods for nonstationary and strictly stationary GARCH parameters with nonparametric long …

Persistent link: https://www.econbiz.de/10009719116

Policy choice in time series by empirical welfare maximization

Kitagawa, Toru; Wang, Weining; Xu, Mengshan - 2024

This paper develops a novel method for policy choice in a dynamic setting where the available data is a multi-variate time series. Building on the statistical treatment choice framework, we propose Time-series Empirical Welfare Maximization (T-EWM) methods to estimate an optimal policy rule by...

Persistent link: https://www.econbiz.de/10015168545

Sieve inference on semi-nonparametric time series models

Chen, Xiaohong; Liao, Zhipeng; Sun, Yixiao - 2012

The method of sieves has been widely used in estimating semiparametric and nonparametric models. In this paper, we first provide a general theory on the asymptotic normality of plug-in sieve M estimators of possibly irregular functionals of semi/nonparametric time series models. Next, we...

Persistent link: https://www.econbiz.de/10009504597

Nonparametric estimation of finite mixtures

Bonhomme, Stéphane; Jochmans, Koen; Robin, Jean-Marc - 2014 - rev.

The aim of this paper is to provide simple nonparametric methods to estimate finitemixture models from data with repeated measurements. Three measurements suffice for the mixture to be fully identified and so our approach can be used even with very short panel data. We provide distribution...

Persistent link: https://www.econbiz.de/10010254835

Optimal bandwidth selection for robust generalized method of moments estimation

Wilhelm, Daniel - 2014

A two-step generalized method of moments estimation procedure can be made robust to heteroskedasticity and …

Persistent link: https://www.econbiz.de/10010336485

Nonparametric regression for locally stationary time series

Vogt, Michael - 2012

time-varying additive components. As will be seen, estimation in these models does not su er from the curse of …

Persistent link: https://www.econbiz.de/10009614397