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Jump variation estimation with noisy high frequency financial data via wavelets

Zhang, Xin; Kim, Donggyu; Wang, Yazhen - In: Econometrics : open access journal 4 (2016) 3, pp. 1-26

-step procedure with detection and estimation. In Step 1, we detect the jump locations by performing wavelet transformation on the … observed noisy price processes. Since wavelet coefficients are significantly larger at the jump locations than the others, we … calibrate the wavelet coefficients through a threshold and declare jump points if the absolute wavelet coefficients exceed the …

Persistent link: https://www.econbiz.de/10011568279

Integrated ARCH, FIGARCH and AR models : origins of long memory

Giraitis, Liudas; Surgailis, Donatas; Škarnulis, Andrius - 2015

Although the properties of the ARCH(∞) model are well investigated, the existence of long memory FIGARCH and IARCH solution was not established in the literature. These two popular ARCH type models which are widely used in applied literature, were causing theoretical controversy because of the...

Persistent link: https://www.econbiz.de/10011405303

Long-run trends and cycles in US house prices

Caporale, Guglielmo Maria; Gil-Alaña, Luis A. - 2023

This paper analyses US nominal house prices at an annual frequency over the period from 1927 to 2022 by means of a very general time series model. This includes both a (linear and non-linear) deterministic and a stochastic component, with the latter allowing for fractional orders of integration...

Persistent link: https://www.econbiz.de/10014427184

Nonparametric Estimation of the Volatility Under Microstructure Noise : Wavelet Adaptation

Hoffmann, Marc - 2010

wavelet thresholding, we construct adaptive estimators that achieve a nearly optimal rate within a large scale of smoothness …

Persistent link: https://www.econbiz.de/10013139169

The influence of additive outliers on the performance of information criteria to detect nonlinearity

Rinke, Saskia - 2016

In this paper the performance of information criteria and a test against SETAR nonlinearity for outlier contaminated time series are investigated. Additive outliers can seriously influence the properties of the underlying time series and hence of linearity tests, resulting in spurious test...

Persistent link: https://www.econbiz.de/10011488709

Evolutionary sequential Monte Carlo samplers for change-point models

Dufays, Arnaud - In: Econometrics : open access journal 4 (2016) 1, pp. 1-33

Sequential Monte Carlo (SMC) methods are widely used for non-linear filtering purposes. However, the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov-Chain Monte-Carlo (MCMC) methods. Not only do SMC...

Persistent link: https://www.econbiz.de/10011504888

Information criteria for nonlinear time series models

Rinke, Saskia; Sibbertsen, Philipp - 2015

In this paper the performance of different information criteria for simultaneous model class and lag order selection is evaluated using simulation studies. We focus on the ability of the criteria to distinguish linear and nonlinear models. In the simulation studies, we consider three different...

Persistent link: https://www.econbiz.de/10010503893

Asymptotic properties of the estimator of the long-run coefficient in a dynamic model with integrated regressors and serially correlated errors

Maekawa, Koichi (contributor); McAleer, Michael (contributor) - 2001 - [Elektronische Ressource]

In this paper we examine the asymptotic properties of the estimator of the long-run coefficient (LRC) in a dynamic regression model with integrated regressors and serially correlated errors. We show that the OLS estimators of the regression coefficients are inconsistent but the OLS-based...

Persistent link: https://www.econbiz.de/10001644304

Evolutionary Sequential Monte Carlo Samplers for Change-Point Models

Dufays, Arnaud - 2018

Sequential Monte Carlo (SMC) methods are widely used for non-linear filtering purposes. Nevertheless the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov-Chain Monte-Carlo (MCMC) methods. Not only SMC...

Persistent link: https://www.econbiz.de/10012936969

Joint Bayesian Analysis of Parameters and States in Nonlinear, Non-Gaussian State Space Models

Barra, Istvan - 2016

We propose a new methodology for designing flexible proposal densities for the joint posterior density of parameters and states in a nonlinear, non-Gaussian state space model. We show that a highly efficient Bayesian procedure emerges when these proposal densities are used in an independent...

Persistent link: https://www.econbiz.de/10013005987

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