Can we Improve Understanding of the Financial Market Dependencies in the Crisis by their Decomposition?

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F13%3A00396003" target="_blank" >RIV/67985556:_____/13:00396003 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Can we Improve Understanding of the Financial Market Dependencies in the Crisis by their Decomposition?

Popis výsledku v původním jazyce

Study of the financial market dependencies have become one of the most active and successful areas of research in the time series econometrics and economic forecasting during the recent decades. Current financial crisis have shown that understanding of the dependencies in the markets is crucial and it has even boosted the interest of researchers. this work brings new theoretical framework for the realized covariation estimation gener- alizing the current knowledge and bringing the estimation to the time-frequency domain for the first time. Usage of wavelets allows us to decompose the correlation measures into several investment horizons. our estimator is moreover able to separate individual jumps, co-jumps and true covariation from the high frequency data, thus brings better understanding of the dependence. the results have crucial impact on the portfolio diver- sification especially in the crisis years as they point to the strong dynamic relationships at various investment horizons.

Název v anglickém jazyce

Can we Improve Understanding of the Financial Market Dependencies in the Crisis by their Decomposition?

Popis výsledku anglicky

Study of the financial market dependencies have become one of the most active and successful areas of research in the time series econometrics and economic forecasting during the recent decades. Current financial crisis have shown that understanding of the dependencies in the markets is crucial and it has even boosted the interest of researchers. this work brings new theoretical framework for the realized covariation estimation gener- alizing the current knowledge and bringing the estimation to the time-frequency domain for the first time. Usage of wavelets allows us to decompose the correlation measures into several investment horizons. our estimator is moreover able to separate individual jumps, co-jumps and true covariation from the high frequency data, thus brings better understanding of the dependence. the results have crucial impact on the portfolio diver- sification especially in the crisis years as they point to the strong dynamic relationships at various investment horizons.

Druh

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

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název periodika

ACTA VŠFS

ISSN

1802-792X

e-ISSN

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Svazek periodika

7

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

25

Strana od-do

6-30

Kód UT WoS článku

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EID výsledku v databázi Scopus

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