Bootstrapping Stationary ARMA-GARCH Models (Record no. 113032)

000 -LEADER
fixed length control field 02283nam a22003975i 4500
001 - CONTROL NUMBER
control field 978-3-8348-9778-7
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140220084553.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 101031s2010 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783834897787
-- 978-3-8348-9778-7
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-8348-9778-7
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA1-939
072 #7 - SUBJECT CATEGORY CODE
Subject category code PB
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code MAT000000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 510
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Shimizu, Kenichi.
Relator term author.
245 10 - TITLE STATEMENT
Title Bootstrapping Stationary ARMA-GARCH Models
Medium [electronic resource] /
Statement of responsibility, etc by Kenichi Shimizu.
264 #1 -
-- Wiesbaden :
-- Vieweg+Teubner,
-- 2010.
300 ## - PHYSICAL DESCRIPTION
Extent 148 p. 12 illus.
Other physical details online resource.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Bootstrap Does not Always Work -- Parametric AR(p)-ARCH(q) Models -- Parametric ARMA(p, q)- GARCH(r, s) Models -- Semiparametric AR(p)-ARCH(1) Models.
520 ## - SUMMARY, ETC.
Summary, etc Bootstrap technique is a useful tool for assessing uncertainty in statistical estimation and thus it is widely applied for risk management. Bootstrap is without doubt a promising technique, however, it is not applicable to all time series models. A wrong application could lead to a false decision to take too much risk. Kenichi Shimizu investigates the limit of the two standard bootstrap techniques, the residual and the wild bootstrap, when these are applied to the conditionally heteroscedastic models, such as the ARCH and GARCH models. The author shows that the wild bootstrap usually does not work well when one estimates conditional heteroscedasticity of Engle’s ARCH or Bollerslev’s GARCH models while the residual bootstrap works without problems. Simulation studies from the application of the proposed bootstrap methods are demonstrated together with the theoretical investigation.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematics.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematics.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematics, general.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783834809926
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-8348-9778-7
912 ## -
-- ZDB-2-SMA

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