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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

Finite sample accuracy of integrated volatility estimators

Nielsen, Morten Ørregaard; Frederiksen, Per - 2005

estimator, and the wavelet estimator, when a typical sample of high-frequency data is observed. We employ several different … volatility process. However, bid-ask bounce effects render realized volatility and especially the wavelet estimator less useful … ; market microstructure ; Monte Carlo simulation ; realized volatility ; wavelet …

Persistent link: https://www.econbiz.de/10003919701

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

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

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

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

A smooth permanent surge process

González, Andrés (contributor) - 2004 - [Elektronische Ressource]

In this paper we introduce the Smooth Permanent Surge [SPS] model. The model is an integrated non lineal moving average process with possibly unit roots in the moving average coefficients. The process nests the Stochastic Permanent Break [STOPBREAK] process by Engle and Smith (1999) and in a...

Persistent link: https://www.econbiz.de/10002465176

GMM Estimation of Fixed Effects Dynamic Panel Data Models with Spatial Lag and Spatial Errors

Čížek, Pavel; Jacobs, Jan; Ligthart, Jenny E.; … - 2015

The three-step generalized methods of moments (GMM) approach of Kapoor, Kelejian and Prucha (2007), which corrects for spatially correlated errors in static panel data models, is extended by introducing fixed effects, a spatial lag, and a one-period lag of the dependent variable as additional...

Persistent link: https://www.econbiz.de/10014175015

Dynamic Panel Data Models Featuring Endogenous Interaction and Spatially Correlated Errors

Jacobs, Jan; Ligthart, Jenny E.; Vrijburg, Hendrik - 2009

We extend the three-step generalized methods of moments (GMM) approach of Kapoor, Kelejian, and Prucha (2007), which corrects for spatially correlated errors in static panel data models, by introducing a spatial lag and a one-period lag of the dependent variable as additional explanatory...

Persistent link: https://www.econbiz.de/10014200234

Markov Chain Monte Carlo Methods for Generalized Stochastic Volatility Models

Chib, Siddhartha; Shephard, Neil; Nardari, Federico - 2001

This paper is concerned with simulation based inference in generalized models of stochastic volatility defined by heavy-tailed student-t distributions (with unknown degrees of freedom) and covariate effects in the observation and volatility equations and a jump component in the observation...

Persistent link: https://www.econbiz.de/10014142429