Estimation in Conditionally Heteroscedastic Time Series Models

Estimation in Conditionally Heteroscedastic Time Series Models
Author :
Publisher : Springer Science & Business Media
Total Pages : 239
Release :
ISBN-10 : 9783540269786
ISBN-13 : 3540269789
Rating : 4/5 (86 Downloads)

Book Synopsis Estimation in Conditionally Heteroscedastic Time Series Models by : Daniel Straumann

Download or read book Estimation in Conditionally Heteroscedastic Time Series Models written by Daniel Straumann and published by Springer Science & Business Media. This book was released on 2006-01-27 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Nowadays ARCH has been replaced by more general and more sophisticated models, such as GARCH (generalized autoregressive heteroscedastic).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.


Estimation in Conditionally Heteroscedastic Time Series Models Related Books

Estimation in Conditionally Heteroscedastic Time Series Models
Language: en
Pages: 239
Authors: Daniel Straumann
Categories: Business & Economics
Type: BOOK - Published: 2006-01-27 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

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 (aut
Modeling Financial Time Series with S-PLUS
Language: en
Pages: 632
Authors: Eric Zivot
Categories: Business & Economics
Type: BOOK - Published: 2013-11-11 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS stat
A Time Series Approach to Option Pricing
Language: en
Pages: 202
Authors: Christophe Chorro
Categories: Business & Economics
Type: BOOK - Published: 2014-12-04 - Publisher: Springer

DOWNLOAD EBOOK

The current world financial scene indicates at an intertwined and interdependent relationship between financial market activity and economic health. This book e
Handbook of Financial Time Series
Language: en
Pages: 1045
Authors: Torben Gustav Andersen
Categories: Business & Economics
Type: BOOK - Published: 2009-04-21 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical poin
GARCH Models
Language: en
Pages: 507
Authors: Christian Francq
Categories: Mathematics
Type: BOOK - Published: 2019-03-19 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Provides a comprehensive and updated study of GARCH models and their applications in finance, covering new developments in the discipline This book provides a c