Application Of Data Mining Techniques For
Understanding Capital Structure Of
Brazilian Companies
Author(s)
R. A. M. Horta, H. M. Pires & B. S. L. P. de Lima
Abstract
The capital structure decision is related to the adoption of strategies for the
choice of financing sources for the own capital and the thirty party capital.
Numerous studies were developed aiming at clarifying the adoption of those
strategies.
This paper aims to identify attributes that influence the decision of capital
structure through an exploratory data analysis using records of Brazilian
companies of open capital. The financial companies were not included in this
study. Thus, it is expected to achieve new information on this process of
knowledge discovery through statistical and data mining techniques, such as
linear regression, robust regression and neural networks, in order to get a better
assessment of the financing strategies employed by companies.
The data analysis was made in two stages employing as dependent variables
the onerous debt and the equity degree of financial leverage. The database
consists of companies on BOVESPA classified by economic sectors in the period
from 1996 to 2006.
The results suggest that the explanatory variables of financial leverage are:
economic sector; return on equity; return on assets; immediate liquidity; general
liquidity and assets turnover.
Keywords: data mining, capital structure, attribute selection.
Keywords
data mining, capital structure, attribute selection.
Related Book
Other papers in this volume
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