Estimation in Conditionally Heteroscedastic Time Series Models
In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatility. Engle showed that this model, which he called ARCH (autoregressive conditionally heteroscedastic), is well-suited for the description of economic and financial price. Nowadays ARCH has been repla...
Gorde:
| Egile nagusia: | |
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| Formatua: | Livre numérique |
| Hizkuntza: | Anglais |
| Argitaratua: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
2005.
Cham : Springer Nature |
| Saila: | Lecture Notes in Statistics
181 |
| Sarrera elektronikoa: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Oharra: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Estimation in Conditionally Heteroscedastic Time Series Models, Texte imprimé, 9783540211358 • Estimation in Conditionally Heteroscedastic Time Series Models, Texte imprimé, 9783540801061 |
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| 009 | PPN123083567 | ||
| 020 | |a 9783540269786 (PDF) | ||
| 041 | 0 | |a eng | |
| 082 | |a 330.015195 | ||
| 100 | 1 | |a Straumann, Daniel. | |
| 245 | 1 | 0 | |a Estimation in Conditionally Heteroscedastic Time Series Models |c by Daniel Straumann. |
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c 2005. | ||
| 490 | 0 | |a Lecture Notes in Statistics |v 181 |x 2197-7186 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 0 | |a Some Mathematical Tools -- Financial Time Series: Facts and Models -- Parameter Estimation: An Overview -- Quasi Maximum Likelihood Estimation in Conditionally Heteroscedastic Time Series Models: A Stochastic Recurrence Equations Approach -- Maximum Likelihood Estimation in Conditionally Heteroscedastic Time Series Models -- Quasi Maximum Likelihood Estimation in a Generalized Conditionally Heteroscedastic Time Series Model with Heavy tailed Innovations -- Whittle Estimation in a Heavy tailed GARCH(1,1) Model. | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. chttps://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatility. Engle showed that this model, which he called ARCH (autoregressive conditionally heteroscedastic), is well-suited for the description of economic and financial price. Nowadays ARCH has been replaced by more general and more sophisticated models, such as GARCH (generalized autoregressive heteroscedastic). This monograph concentrates on mathematical statistical problems associated with fitting conditionally heteroscedastic time series models to data. This includes the classical statistical issues of consistency and limiting distribution of estimators. Particular attention is addressed to (quasi) maximum likelihood estimation and misspecified models, along to phenomena due to heavy-tailed innovations. The used methods are based on techniques applied to the analysis of stochastic recurrence equations. Proofs and arguments are given wherever possible in full mathematical rigour. Moreover, the theory is illustrated by examples and simulation studies. | ||
| 776 | 0 | |t Estimation in Conditionally Heteroscedastic Time Series Models |b Texte imprimé |z 9783540211358 | |
| 776 | 0 | |t Estimation in Conditionally Heteroscedastic Time Series Models |b Texte imprimé |z 9783540801061 | |
| 856 | 4 | |q PDF |u https://doi.org/10.1007/b138400 |z Accès sur la plateforme de l'éditeur | |
| 856 | 4 | |u https://revue-sommaire.istex.fr/ark:/67375/8Q1-28C31XJG-6 |z Accès sur la plateforme Istex | |
| 856 | 4 | |5 452349901:748045511 |u https://ezproxy.univ-orleans.fr/login?url=https://doi.org/10.1007/b138400 |z Accès Université d'Orléans | |
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