Estimation of long memory in volatility using wavelets

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00478480" target="_blank" >RIV/67985556:_____/17:00478480 - isvavai.cz</a>

Alternative codes found

RIV/00216208:11230/17:10363572

Result on the web

<a href="http://dx.doi.org/10.1515/snde-2016-0101" target="_blank" >http://dx.doi.org/10.1515/snde-2016-0101</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1515/snde-2016-0101" target="_blank" >10.1515/snde-2016-0101</a>

Result language

angličtina

Original language name

Estimation of long memory in volatility using wavelets

Original language description

This work studies wavelet-based Whittle estimator of the fractionally integrated exponential gen- eralized autoregressive conditional heteroscedasticity (FIEGARCH) model often used for modeling long memory in volatility of financial assets. The newly proposed estimator approximates the spectral density using wavelet transform, which makes it more robust to certain types of irregularities in data. Based on an extensive Monte Carlo study, both behavior of the proposed estimator and its relative performance with respect to traditional estimators are assessed. In addition, we study properties of the estimators in presence of jumps, which brings interesting discussion. We find that wavelet-based estimator may become an attrac- tive robust and fast alternative to the traditional methods of estimation. In particular, a localized version of our estimator becomes attractive in small samples.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

50202 - Applied Economics, Econometrics

Project

<a href="/en/project/GA13-32263S" target="_blank" >GA13-32263S: Multivariate spectral analysis of financial markets</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Studies in Nonlinear Dynamics and Econometrics

ISSN

1081-1826

e-ISSN

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Volume of the periodical

21

Issue of the periodical within the volume

3

Country of publishing house

US - UNITED STATES

Number of pages

22

Pages from-to

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UT code for WoS article

000411276100002

EID of the result in the Scopus database

2-s2.0-85021440941