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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...
| Call Number: | Libro Electrónico |
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| Main Author: | |
| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | Inglés |
| Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2005.
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| Edition: | 1st ed. 2005. |
| Series: | Lecture Notes in Statistics,
181 |
| Subjects: | |
| Online Access: | Texto Completo |
Table of Contents:
- 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.