Robust recursive estimation for financial time series

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10386862" target="_blank" >RIV/00216208:11320/18:10386862 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Robust recursive estimation for financial time series

Original language description

The generalized autoregressive conditional heteroscedasticity (GARCH) process is a particular modelling scheme, which is capable of forecasting the current level of volatility of financial time series. Recently, recursive estimation methods suitable for this class of stochastic processes have been introduced in the literature. They undoubtedly represent attractive alternatives to the standard non-recursive estimation procedures with many practical applications. It is truly advantageous to adopt numerically effective estimation techniques that can estimate and control such models in real time. However, abnormal observations (outliers) may occur in data. They may be caused by many reasons, e.g. by additive errors, measurement failures or management actions. Exceptional data points will influence the model estimation considerably if no specific action is taken. The aim of this contribution is to propose and examine a robust recursive estimation algorithm suitable for GARCH models. It seems to be useful for various financial time series, in particular for (high-frequency) financial returns contaminated by additive outliers. The introduced algorithm can be effective in the risk control and regulation when the prediction of volatility is the main concern since it distinguishes and corrects outlaid bursts of volatility. Real data examples are presented.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10103 - Statistics and probability

Project

<a href="/en/project/GA17-00676S" target="_blank" >GA17-00676S: Dynamic models of risk in finance and insurance</a><br>

Continuities

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

Publication year

2018

Confidentiality

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

Article name in the collection

Conference Proceedings

ISBN

978-80-87990-14-8

ISSN

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e-ISSN

neuvedeno

Number of pages

9

Pages from-to

563-571

Publisher name

Melandrium

Place of publication

Praha

Event location

Praha

Event date

Sep 6, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000455809400056