Wavelet Co-movement Significance Testing with Respect to Gaussian White Noise Background

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU124855" target="_blank" >RIV/00216305:26220/18:PU124855 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.itm-conferences.org/articles/itmconf/abs/2018/01/contents/contents.html" target="_blank" >https://www.itm-conferences.org/articles/itmconf/abs/2018/01/contents/contents.html</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1051/itmconf/20181601002" target="_blank" >10.1051/itmconf/20181601002</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Wavelet Co-movement Significance Testing with Respect to Gaussian White Noise Background

Popis výsledku v původním jazyce

The paper deals with significance testing of time series co-movement measured via time-frequency approach. We use the wavelet analysis for estimation of the co/cross-spectra for the co-movement analysis. This technique is very popular in the most of economic applications for its better time resolution compare to other techniques. Such approach put in evidence the existence of both long-run and short-run co-movement. In order to have better predictive power it is suitable to support and validate obtained results via some testing approach. We investigate the test of wavelet power co/cross-spectrum with respect to the Gaussian white noise background with the use of the Bessel function. Our experiment is performed on synthetic signal and real data. We use seasonally adjusted quarterly data of gross domestic product of the United Kingdom, Korea and G7 countries. To validate the test results we perform Monte Carlo simulation. We describe the advantages and disadvantages of both approaches and formulate recommendations for using time-frequency testing for wavelet co/cross-spectra.

Název v anglickém jazyce

Wavelet Co-movement Significance Testing with Respect to Gaussian White Noise Background

Popis výsledku anglicky

The paper deals with significance testing of time series co-movement measured via time-frequency approach. We use the wavelet analysis for estimation of the co/cross-spectra for the co-movement analysis. This technique is very popular in the most of economic applications for its better time resolution compare to other techniques. Such approach put in evidence the existence of both long-run and short-run co-movement. In order to have better predictive power it is suitable to support and validate obtained results via some testing approach. We investigate the test of wavelet power co/cross-spectrum with respect to the Gaussian white noise background with the use of the Bessel function. Our experiment is performed on synthetic signal and real data. We use seasonally adjusted quarterly data of gross domestic product of the United Kingdom, Korea and G7 countries. To validate the test results we perform Monte Carlo simulation. We describe the advantages and disadvantages of both approaches and formulate recommendations for using time-frequency testing for wavelet co/cross-spectra.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

ITM Web of Conferences

ISBN

—

ISSN

2271-2097

e-ISSN

—

Počet stran výsledku

5

Strana od-do

1-5

Název nakladatele

Helenic Military Academy

Místo vydání

Athens, Greece

Místo konání akce

Atény

Datum konání akce

6. 10. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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