Comparing Various EWMA Model Estimators: Value at Risk Perspective

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10329025" target="_blank" >RIV/00216208:11320/16:10329025 - 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

Comparing Various EWMA Model Estimators: Value at Risk Perspective

Popis výsledku v původním jazyce

The exponentially weighted moving average (EWMA) model is a particular modelling scheme supported 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, several on-line (i.e. recursive) estimation techniques suitable for this class of stochastic models have been introduced. These methods undoubtedly represent attractive alternatives to the common identification and calibration procedures (i.e. off-line or batch); they can estimate and control the process behaviour in real time. The aim of the paper is to examine different EWMA model estimators by using financial data. For instance, one might consider the Value at Risk (VaR) backtesting approach since Value at Risk predictions are relevant outputs of the RiskMetrics EWMA modelling framework (especially from the practical point of view). Therefore, various VaR backtests can be used to study the adequacy of different EWMA model estimators.

Název v anglickém jazyce

Comparing Various EWMA Model Estimators: Value at Risk Perspective

Popis výsledku anglicky

The exponentially weighted moving average (EWMA) model is a particular modelling scheme supported 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, several on-line (i.e. recursive) estimation techniques suitable for this class of stochastic models have been introduced. These methods undoubtedly represent attractive alternatives to the common identification and calibration procedures (i.e. off-line or batch); they can estimate and control the process behaviour in real time. The aim of the paper is to examine different EWMA model estimators by using financial data. For instance, one might consider the Value at Risk (VaR) backtesting approach since Value at Risk predictions are relevant outputs of the RiskMetrics EWMA modelling framework (especially from the practical point of view). Therefore, various VaR backtests can be used to study the adequacy of different EWMA model estimators.

Druh

D - Stať ve sborníku

CEP obor

BA - Obecná matematika

OECD FORD obor

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Projekt

<a href="/cs/project/GBP402%2F12%2FG097" target="_blank" >GBP402/12/G097: DYME-Dynamické modely v ekonomii</a><br>

Návaznosti

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

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

34TH INTERNATIONAL CONFERENCE MATHEMATICAL METHODS IN ECONOMICS (MME 2016)

ISBN

978-80-7494-296-9

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

265-270

Název nakladatele

TECHNICAL UNIVERSITY LIBEREC

Místo vydání

LIBEREC

Místo konání akce

Liberec

Datum konání akce

6. 9. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000385239500046