Asia Pacific University Library catalogue


MODELLING AN EARLY WARNING SYSTEM FOR SYSTEMIC BANKING CRISES / (Record no. 383858)

000 -LEADER
fixed length control field 02756nam a2200217 4500
003 - CONTROL NUMBER IDENTIFIER
control field APU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230317141238.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220211b ||||| |||| 00| 0 eng d
050 ## - LIBRARY OF CONGRESS CALL NUMBER
Classification number PHD-20-22
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name DOONESHSINGH AUDIT (TP053542)
9 (RLIN) 45214
245 12 - TITLE STATEMENT
Title MODELLING AN EARLY WARNING SYSTEM FOR SYSTEMIC BANKING CRISES /
Statement of responsibility, etc DOONESHSINGH AUDIT.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Kuala Lumpur :
Name of publisher, distributor, etc Asia Pacific University,
Date of publication, distribution, etc 2022.
300 ## - PHYSICAL DESCRIPTION
Extent xv, 267 pages :
Other physical details illustrations ;
Dimensions 30 cm.
502 ## - DISSERTATION NOTE
Dissertation note A thesis submitted in fulfillment of the requirements of Asia Pacific University of Technology and Innovation for the award of Doctor of Philosophy in Finance (UCPF1810FIN).
520 ## - SUMMARY, ETC.
Summary, etc The current study pursued a research agenda in view of improving the modelling of Early Warning System (EWS) for systemic banking crises by examining the causes for the failure of existing EWS models prior to the global financial crisis of 2008 (GFC 2008) as well as the novel findings in the aftermath of the GFC 2008. Using a sample of 18 Developed countries that were hit by the GFC 2008 and three control case countries of similar profile, the current study examined the robustness of EWS indicators considered in the aftermath of GFC 2008 and identified new EWS indicators through the application of three main methods of investigation, namely, the ‘Signal extraction’ approach, the Multivariate probit panel regression method, and the Binary Recursive Tree technique, supplemented by the application of a Vector Autoregressive model as well as statistical and balance sheet analysis. In the post-GFC 2008 era, several studies highlighted excessive credit growth as the primary source of vulnerability to the financial system. The current study suggested moving a step further in that what also mattered was where the credit flowed, both to and from. <br/><br/>In view of improving prediction of systemic banking crises, the proposed list of EWS indicators were integrated into a comprehensive EWS model for systemic banking crises that comprised of six main areas of surveillance. The proposed EWS model broadens the scope of surveillance from the narrow realm of key macroeconomic developments and the evolution of vital banking sector metrics to six main areas of interest that add the incidence of excessive growth in credit, asset price growth, expansion in shadow banking activities, and global liquidity, along with global exposure of banks, into the comprehensive EWS model.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Financial crises
9 (RLIN) 14822
General subdivision Forecasting
Geographic subdivision Developing countries.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Financial crises
9 (RLIN) 47799
General subdivision Research
Geographic subdivision Developing countries.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Banks and banking
9 (RLIN) 47800
General subdivision Research
Geographic subdivision Developing countries.
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Prof. Nafis Alam
Relator term Supervisor.
-- 48292
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type PhD Theses
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Use restrictions Not for loan Collection code Home library Current library Shelving location Date acquired Full call number Barcode Date last seen Copy number Koha item type
Not Withdrawn Available   Not Damaged Restricted access Not for loan PhD Theses APU Library APU Library Reference Collection 08/09/2022 PHD-20-22 00019051 17/03/2023 1 Reference