Geometric approach to static and dynamic measurements of risk, bankruptcy and market ranking

This thesis presents two new geometric techniques for empirical analysis of financial data with empirical application on bankruptcy risk prediction. Within these frameworks, we propose the use of new ratio representations (index), the Risk Box measure (RB) and the Dynamic Risk Space (DRS). We also d...

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Main Author:	Bahiraie, Alireza
Format:	Thesis
Language:	English English
Published:	2010
Subjects:	Geometric analysis Bankruptcy Risk
Online Access:	http://psasir.upm.edu.my/id/eprint/22126/1/IPM%202010%2020R.pdf
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id	my-upm-ir.22126
record_format	uketd_dc
spelling	my-upm-ir.221262013-06-20T03:43:19Z Geometric approach to static and dynamic measurements of risk, bankruptcy and market ranking 2010-03 Bahiraie, Alireza This thesis presents two new geometric techniques for empirical analysis of financial data with empirical application on bankruptcy risk prediction. Within these frameworks, we propose the use of new ratio representations (index), the Risk Box measure (RB) and the Dynamic Risk Space (DRS). We also demonstrate the application of these geometric approaches for variable transformation and data visualization at different stages of corporate bankruptcy prediction models based on financial balance sheet. The different stages involved are the selection of variables (predictors), accuracy of each estimation model and the representation of each model for the transformed and common ratios. We provide evidence of the extent to which changes in values of this index are associated with changes in each axis values and how this may alter our economic interpretation of the patterns and direction of risk components. Results of Multiple Discriminant Analysis (MDA), Logistic Analysis (LA) and Genetic Programming (GP) and Logistic Robust statistics are obtained and compared as different classification models. Empirical results show that these classifiers with common ratio are outperformed by the transformed ratios. The Risk Box (RB)and Dynamic Risk Space (DRS) methodologies would be a general methodological guideline associated with financial data, including solving some methodological problems concerning financial ratios such as non-proportion,non-symmetric, non-scaled as illustrated in this thesis for bankruptcy prediction. In this research, the first geometric methodology for financial risk measurement is developed for financial concepts, focusing on theoretical bases rather than isolated facts of financial risk management. Subsequently, this study provides the first graphical financial risk ranking software, named as Dynamic Geometric Risk Space Software (DGRSS). This software provides visualization of risk factors and market ranking. It is ideal for public and private investors, banks, market analysts, companies and stock markets and compatible with any country/sector dataset based on DRS method. Lastly in this research, the Logistic Robust Regression is applied to bankruptcy data for the first time to handle outliers and to obtain more accurate predictions. Geometric analysis Bankruptcy Risk 2010-03 Thesis http://psasir.upm.edu.my/id/eprint/22126/ http://psasir.upm.edu.my/id/eprint/22126/1/IPM%202010%2020R.pdf application/pdf en public phd doctoral Universiti Putra Malaysia Geometric analysis Bankruptcy Risk Institute for Mathematical Research English
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English English
topic	Geometric analysis Bankruptcy Risk
spellingShingle	Geometric analysis Bankruptcy Risk Bahiraie, Alireza Geometric approach to static and dynamic measurements of risk, bankruptcy and market ranking
description	This thesis presents two new geometric techniques for empirical analysis of financial data with empirical application on bankruptcy risk prediction. Within these frameworks, we propose the use of new ratio representations (index), the Risk Box measure (RB) and the Dynamic Risk Space (DRS). We also demonstrate the application of these geometric approaches for variable transformation and data visualization at different stages of corporate bankruptcy prediction models based on financial balance sheet. The different stages involved are the selection of variables (predictors), accuracy of each estimation model and the representation of each model for the transformed and common ratios. We provide evidence of the extent to which changes in values of this index are associated with changes in each axis values and how this may alter our economic interpretation of the patterns and direction of risk components. Results of Multiple Discriminant Analysis (MDA), Logistic Analysis (LA) and Genetic Programming (GP) and Logistic Robust statistics are obtained and compared as different classification models. Empirical results show that these classifiers with common ratio are outperformed by the transformed ratios. The Risk Box (RB)and Dynamic Risk Space (DRS) methodologies would be a general methodological guideline associated with financial data, including solving some methodological problems concerning financial ratios such as non-proportion,non-symmetric, non-scaled as illustrated in this thesis for bankruptcy prediction. In this research, the first geometric methodology for financial risk measurement is developed for financial concepts, focusing on theoretical bases rather than isolated facts of financial risk management. Subsequently, this study provides the first graphical financial risk ranking software, named as Dynamic Geometric Risk Space Software (DGRSS). This software provides visualization of risk factors and market ranking. It is ideal for public and private investors, banks, market analysts, companies and stock markets and compatible with any country/sector dataset based on DRS method. Lastly in this research, the Logistic Robust Regression is applied to bankruptcy data for the first time to handle outliers and to obtain more accurate predictions.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Bahiraie, Alireza
author_facet	Bahiraie, Alireza
author_sort	Bahiraie, Alireza
title	Geometric approach to static and dynamic measurements of risk, bankruptcy and market ranking
title_short	Geometric approach to static and dynamic measurements of risk, bankruptcy and market ranking
title_full	Geometric approach to static and dynamic measurements of risk, bankruptcy and market ranking
title_fullStr	Geometric approach to static and dynamic measurements of risk, bankruptcy and market ranking
title_full_unstemmed	Geometric approach to static and dynamic measurements of risk, bankruptcy and market ranking
title_sort	geometric approach to static and dynamic measurements of risk, bankruptcy and market ranking
granting_institution	Universiti Putra Malaysia
granting_department	Institute for Mathematical Research
publishDate	2010
url	http://psasir.upm.edu.my/id/eprint/22126/1/IPM%202010%2020R.pdf
_version_	1747811519903563776

Geometric approach to static and dynamic measurements of risk, bankruptcy and market ranking

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