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Statistical modelling to predict corporate default for Brazilian companies in the context of Basel II using a new set of financial ratios

Research output: Working paper

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Statistical modelling to predict corporate default for Brazilian companies in the context of Basel II using a new set of financial ratios. / Minussi, J; Soopramanien, D G R; Worthington, D J.

Lancaster University : The Department of Management Science, 2007. (Management Science Working Paper Series).

Research output: Working paper

Harvard

Minussi, J, Soopramanien, DGR & Worthington, DJ 2007 'Statistical modelling to predict corporate default for Brazilian companies in the context of Basel II using a new set of financial ratios' Management Science Working Paper Series, The Department of Management Science, Lancaster University.

APA

Vancouver

Minussi J, Soopramanien DGR, Worthington DJ. Statistical modelling to predict corporate default for Brazilian companies in the context of Basel II using a new set of financial ratios. Lancaster University: The Department of Management Science. 2007. (Management Science Working Paper Series).

Author

Minussi, J ; Soopramanien, D G R ; Worthington, D J. / Statistical modelling to predict corporate default for Brazilian companies in the context of Basel II using a new set of financial ratios. Lancaster University : The Department of Management Science, 2007. (Management Science Working Paper Series).

Bibtex

@techreport{2eae12298137467cbf83950427db5be6,
title = "Statistical modelling to predict corporate default for Brazilian companies in the context of Basel II using a new set of financial ratios",
abstract = "This paper deals with statistical modelling to predict failure of Brazilian companies in the light of the Basel II definition of default using a new set of explanatory variables. A rearrangement in the official format of the Balance Sheet is put forward. From this rearrangement a framework of complementary non-conventional ratios is proposed. Initially, a model using 22 traditional ratios is constructed. Problems associated with multicollinearity were found in this model. Adding a group of 6 non-conventional ratios alongside traditional ratios improves the model substantially. The main findings in this study are: (a) logistic regression performs well in the context of Basel II, yielding a sound model applicable in the decision making process; (b) the complementary list of financial ratios plays a critical role in the model proposed; (c) the variables selected in the model show that when current assets and current liabilities are split into two sub-groups - financial and operational - they are more effective in explaining default than the traditional ratios associated with liquidity; and (d) those variables also indicate that high interest rates in Brazil adversely affect the performance of those companies which have a higher dependency on borrowing.",
keywords = "Default prediction, statistical modelling, non-conventional financial ratios, Basel II, Brazilian context.",
author = "J Minussi and Soopramanien, {D G R} and Worthington, {D J}",
year = "2007",
language = "English",
series = "Management Science Working Paper Series",
publisher = "The Department of Management Science",
type = "WorkingPaper",
institution = "The Department of Management Science",

}

RIS

TY - UNPB

T1 - Statistical modelling to predict corporate default for Brazilian companies in the context of Basel II using a new set of financial ratios

AU - Minussi, J

AU - Soopramanien, D G R

AU - Worthington, D J

PY - 2007

Y1 - 2007

N2 - This paper deals with statistical modelling to predict failure of Brazilian companies in the light of the Basel II definition of default using a new set of explanatory variables. A rearrangement in the official format of the Balance Sheet is put forward. From this rearrangement a framework of complementary non-conventional ratios is proposed. Initially, a model using 22 traditional ratios is constructed. Problems associated with multicollinearity were found in this model. Adding a group of 6 non-conventional ratios alongside traditional ratios improves the model substantially. The main findings in this study are: (a) logistic regression performs well in the context of Basel II, yielding a sound model applicable in the decision making process; (b) the complementary list of financial ratios plays a critical role in the model proposed; (c) the variables selected in the model show that when current assets and current liabilities are split into two sub-groups - financial and operational - they are more effective in explaining default than the traditional ratios associated with liquidity; and (d) those variables also indicate that high interest rates in Brazil adversely affect the performance of those companies which have a higher dependency on borrowing.

AB - This paper deals with statistical modelling to predict failure of Brazilian companies in the light of the Basel II definition of default using a new set of explanatory variables. A rearrangement in the official format of the Balance Sheet is put forward. From this rearrangement a framework of complementary non-conventional ratios is proposed. Initially, a model using 22 traditional ratios is constructed. Problems associated with multicollinearity were found in this model. Adding a group of 6 non-conventional ratios alongside traditional ratios improves the model substantially. The main findings in this study are: (a) logistic regression performs well in the context of Basel II, yielding a sound model applicable in the decision making process; (b) the complementary list of financial ratios plays a critical role in the model proposed; (c) the variables selected in the model show that when current assets and current liabilities are split into two sub-groups - financial and operational - they are more effective in explaining default than the traditional ratios associated with liquidity; and (d) those variables also indicate that high interest rates in Brazil adversely affect the performance of those companies which have a higher dependency on borrowing.

KW - Default prediction

KW - statistical modelling

KW - non-conventional financial ratios

KW - Basel II

KW - Brazilian context.

M3 - Working paper

T3 - Management Science Working Paper Series

BT - Statistical modelling to predict corporate default for Brazilian companies in the context of Basel II using a new set of financial ratios

PB - The Department of Management Science

CY - Lancaster University

ER -