Arbeitspapier
Tempered stable and tempered infinitely divisible GARCH models
In this paper, we introduce a new GARCH model with an infinitely divisible distributed innovation, referred to as the rapidly decreasing tempered stable (RDTS) GARCH model. This model allows the description of some stylized empirical facts observed for stock and index returns, such as volatility clustering, the non-zero skewness and excess kurtosis for the residual distribution. Furthermore, we review the classical tempered stable (CTS) GARCH model, which has similar statistical properties. By considering a proper density transformation between infinitely divisible random variables, these GARCH models allow to find the risk-neutral price process, and hence they can be applied to option pricing. We propose algorithms to generate scenario based on GARCH models with CTS and RDTS innovation. To investigate the performance of these GARCH models, we report a parameters estimation for Dow Jones Industrial Average (DJIA) index and stocks included in this index, and furthermore to demonstrate their advantages, we calculate option prices based on these models. It should be noted that only historical data on the underlying asset and on the riskfree rate are taken into account to evaluate option prices.
- Sprache
-
Englisch
- Erschienen in
-
Series: KIT Working Paper Series in Economics ; No. 28
- Klassifikation
-
Wirtschaft
- Thema
-
tempered infinitely divisible distribution
tempered stable distribution
rapidly decreasing tempered stable distribution
GARCH model option pricing
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Kim, Young Shin
Rachev, Svetlozar T.
Bianchi, Michele Leonardo
Fabozzi, Frank J.
- Ereignis
-
Veröffentlichung
- (wer)
-
Karlsruher Institut für Technologie (KIT), Institut für Volkswirtschaftslehre (ECON)
- (wo)
-
Karlsruhe
- (wann)
-
2011
- DOI
-
doi:10.5445/IR/1000023239
- Handle
- URN
-
urn:nbn:de:swb:90-232394
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Kim, Young Shin
- Rachev, Svetlozar T.
- Bianchi, Michele Leonardo
- Fabozzi, Frank J.
- Karlsruher Institut für Technologie (KIT), Institut für Volkswirtschaftslehre (ECON)
Entstanden
- 2011
Ähnliche Objekte (12)
Multivariate GARCH models
Evaluating GARCH Models
Evaluating exponential GARCH models
Outlier Detection in GARCH Models
Stability of nonlinear AR-GARCH models
An introduction to univariate GARCH models
Bootstrapping GARCH models under dependent innovations
Misspecification Testing in GARCH-MIDAS Models
Nonlinear GARCH models for highly persistent volatility
Asymptotics for parametric GARCH-in-Mean Models
Parameter estimation in nonlinear AR-GARCH models
Testing for identification in SVAR-GARCH models
Multivariate GARCH models
Evaluating GARCH Models
Evaluating exponential GARCH models
Outlier Detection in GARCH Models
Stability of nonlinear AR-GARCH models
An introduction to univariate GARCH models
Bootstrapping GARCH models under dependent innovations
Misspecification Testing in GARCH-MIDAS Models
Nonlinear GARCH models for highly persistent volatility
Asymptotics for parametric GARCH-in-Mean Models
Parameter estimation in nonlinear AR-GARCH models
Testing for identification in SVAR-GARCH models
Multivariate GARCH models
Evaluating GARCH Models
Evaluating exponential GARCH models
Outlier Detection in GARCH Models
Stability of nonlinear AR-GARCH models
An introduction to univariate GARCH models
Bootstrapping GARCH models under dependent innovations
Misspecification Testing in GARCH-MIDAS Models
Nonlinear GARCH models for highly persistent volatility
Asymptotics for parametric GARCH-in-Mean Models
Parameter estimation in nonlinear AR-GARCH models