On comparing prediction accuracy of various EWMA model estimators

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10365151" target="_blank" >RIV/00216208:11320/17:10365151 - isvavai.cz</a>

Výsledek na webu

<a href="http://fim2.uhk.cz/mme/conferenceproceedings/mme2017_conference_proceedings.pdf" target="_blank" >http://fim2.uhk.cz/mme/conferenceproceedings/mme2017_conference_proceedings.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

On comparing prediction accuracy of various EWMA model estimators

Popis výsledku v původním jazyce

The exponentially weighted moving average (EWMA) model is a particular modelling scheme advocated by RiskMetrics that is capable of predicting the current level of financial time series volatility. It is designed to track changes in conditional variance of financial returns by assigning exponentially decreasing weights to the observed past squared measurements. Recently, a recursive estimation technique suitable for this class of stochastic processes has been introduced and discussed. It represents a computationally attractive alternative to the already established non-recursive estimation strategies since it is effective in terms of memory storage, computational complexity and its ability to estimate and control the EWMA modelling scheme in real time. The aim of the paper is to investigate prediction accuracy of different EWMA model estimators. By analysing a set of eighteen very diverse world stock indices, this study has shown that the recursive estimation scheme can be recommended due to its advantageous properties if predicting the volatility; it is competitive to other approaches commonly used in financial practice.

Název v anglickém jazyce

On comparing prediction accuracy of various EWMA model estimators

Popis výsledku anglicky

The exponentially weighted moving average (EWMA) model is a particular modelling scheme advocated by RiskMetrics that is capable of predicting the current level of financial time series volatility. It is designed to track changes in conditional variance of financial returns by assigning exponentially decreasing weights to the observed past squared measurements. Recently, a recursive estimation technique suitable for this class of stochastic processes has been introduced and discussed. It represents a computationally attractive alternative to the already established non-recursive estimation strategies since it is effective in terms of memory storage, computational complexity and its ability to estimate and control the EWMA modelling scheme in real time. The aim of the paper is to investigate prediction accuracy of different EWMA model estimators. By analysing a set of eighteen very diverse world stock indices, this study has shown that the recursive estimation scheme can be recommended due to its advantageous properties if predicting the volatility; it is competitive to other approaches commonly used in financial practice.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GA17-00676S" target="_blank" >GA17-00676S: Dynamické modely rizika ve financích a pojišťovnictví</a><br>

Návaznosti

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

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 35th International Conference on Mathematical Methods in Economics

ISBN

978-80-7435-678-0

ISSN

—

e-ISSN

neuvedeno

Počet stran výsledku

6

Strana od-do

219-224

Název nakladatele

University of Hradec Králové

Místo vydání

Hradec Králové

Místo konání akce

Hradec Králové (CZ)

Datum konání akce

13. 9. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000427151400038