Realized wavelet-based estimation of integrated variance and jumps in the presence of noise

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F15%3A00434203" target="_blank" >RIV/67985556:_____/15:00434203 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11230/15:10281366

Výsledek na webu

<a href="http://dx.doi.org/10.1080/14697688.2014.950319" target="_blank" >http://dx.doi.org/10.1080/14697688.2014.950319</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/14697688.2014.950319" target="_blank" >10.1080/14697688.2014.950319</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Realized wavelet-based estimation of integrated variance and jumps in the presence of noise

Popis výsledku v původním jazyce

We introduce wavelet-based methodology for estimation of realized variance allowing its mea- surement in the time-frequency domain. Using smooth wavelets and Maximum Overlap Dis- crete Wavelet Transform, we allow for the decomposition of the realized variance into several investment horizons and jumps. Basing our estimator in the two-scale realized variance frame- work, we are able to utilize all available data and get feasible estimator in the presence of microstructure noise as well. The estimator is tested in a large numerical study of the finite sample performance and is compared to other popular realized variation estimators. We use different simulation settings with changing noise as well as jump level in different price pro- cesses including long memory fractional stochastic volatility model. The results reveal that our wavelet-based estimator is able to estimate and forecast the realized measures with the greatest precision.

Název v anglickém jazyce

Realized wavelet-based estimation of integrated variance and jumps in the presence of noise

Popis výsledku anglicky

We introduce wavelet-based methodology for estimation of realized variance allowing its mea- surement in the time-frequency domain. Using smooth wavelets and Maximum Overlap Dis- crete Wavelet Transform, we allow for the decomposition of the realized variance into several investment horizons and jumps. Basing our estimator in the two-scale realized variance frame- work, we are able to utilize all available data and get feasible estimator in the presence of microstructure noise as well. The estimator is tested in a large numerical study of the finite sample performance and is compared to other popular realized variation estimators. We use different simulation settings with changing noise as well as jump level in different price pro- cesses including long memory fractional stochastic volatility model. The results reveal that our wavelet-based estimator is able to estimate and forecast the realized measures with the greatest precision.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

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

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Quantitative Finance

ISSN

1469-7688

e-ISSN

—

Svazek periodika

15

Číslo periodika v rámci svazku

8

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

18

Strana od-do

1347-1364

Kód UT WoS článku

000357669600001

EID výsledku v databázi Scopus

2-s2.0-84936890267