000			02756nam a2200217 4500
003			APU
005			20230317141238.0
008			220211b ||||| |||| 00| 0 eng d
050			_aPHD-20-22
100	0		_aDOONESHSINGH AUDIT (TP053542) _945214
245	1	2	_aMODELLING AN EARLY WARNING SYSTEM FOR SYSTEMIC BANKING CRISES / _cDOONESHSINGH AUDIT.
260			_aKuala Lumpur : _bAsia Pacific University, _c2022.
300			_axv, 267 pages : _billustrations ; _c30 cm.
502			_aA 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			_aThe 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. 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	_aFinancial crises _914822 _xForecasting _zDeveloping countries.
650		0	_aFinancial crises _947799 _xResearch _zDeveloping countries.
650		0	_aBanks and banking _947800 _xResearch _zDeveloping countries.
700			_aProf. Nafis Alam _eSupervisor. _948292
942			_2lcc _cPhD Theses
999			_c383858 _d383858