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E Book

Estimation in Conditionally Heteroscedastic Time Series Models

Straumann, Daniel. - Nama Orang;

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.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 Nowadays ARCH has been replaced by more general and more sophisticated models, such as GARCH (generalized autoregressive heteroscedastic).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.


Ketersediaan
#
Koleksi E Book Belum memasukkan lokasi
9783540269786
Tersedia
Informasi Detail
Judul Seri
-
No. Panggil
-
Penerbit
Berlin, Heidelberg : Springer., 2005
Deskripsi Fisik
XVI, 228 p.online resource.
Bahasa
English
ISBN/ISSN
9783540269786
Klasifikasi
330.015195
Tipe Isi
-
Tipe Media
-
Tipe Pembawa
-
Edisi
1st ed. 2005.
Subjek
Statistics .
Economics, Mathematical .
Quantitative Finance.
Statistics for Business, Management, Economics, Finance, Insurance.
Info Detail Spesifik
-
Pernyataan Tanggungjawab
Daniel Straumann.
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