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Erschienen in:
Exploratory Classification of Time-Series Kapitel lesen Erstes Kapitel lesen

2021 | OriginalPaper | Buchkapitel

Using COGARCH-Filtered Volatility in Modelling Within ARDL Framework

verfasst von : Yakup Arı

Erschienen in: Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics

Verlag: Springer International Publishing

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Abstract

The aim of this chapter is to use volatility data, obtained from Continuous GARCH process, in the ARDL Bounds testing approach. For this purpose, the volatility of financial data is modelled by the Continuous GARCH process which is a generalized solution of Lévy driven stochastic differential equation. The impact of the volatility on another variable is analyzed via ARDL Bounds testing approach that gives the opportunity to analyze the short-run and long-term relation, cointegration between variables. The real data application and the R codes are given as an illustration.

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Vorheriges Kapitel ARCH Models and an Application on Exchange Rate Volatility: ARCH and GARCH Models
Nächstes Kapitel Performance of MS-GARCH Models: Bayesian MCMC-Based Estimation
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Metadaten
Titel
Using COGARCH-Filtered Volatility in Modelling Within ARDL Framework
verfasst von
Yakup Arı
Copyright-Jahr
2021
Verlag
Springer International Publishing
Buch
Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics

Print ISBN: 978-3-030-54107-1

Electronic ISBN: 978-3-030-54108-8

Copyright-Jahr: 2021

DOI
https://doi.org/10.1007/978-3-030-54108-8_13

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