Mathematical and Statistical Methods for Actuarial Sciences and Finance

A simple dimension reduction procedure for corporate

finance composite indicators∗

Marco Marozzi and Luigi Santamaria

Abstract.Financial ratios provide useful quantitative financial information to both investors

and analysts so that they can rate a company. Many financial indicators from accounting books

are taken into account. Instead of sequentially examining each ratio, one can analyse together

different combinations of ratios in order to simultaneously take into account different aspects.

This may be done by computing a composite indicator. The focus of the paper is on reducing the

dimension of a composite indicator. A quick and compact solution is proposed, and a practical

application to corporate finance is presented. In particular, the liquidity issue is addressed. The

results suggest that analysts should take our method into consideration as it is much simpler

than other dimension reduction methods such as principal component or factor analysis and is

therefore much easier to be used in practice by non-statisticians (as financial analysts generally

are). Moreover, the proposed method is always readily comprehended and requires milder

assumptions.

Key words:dimension reduction, composite indicator, financial ratios, liquidity

1 Introduction

Financial ratios provide useful quantitative financial information to both investors and

analysts so that they can rate a company. Many financial indicators fromaccounting

books are taken intoaccount. In general, ratios measuring profitability, liquidity,

solvency and efficiency are considered.

Instead of sequentially examining each ratio, one can analyse different combina-

tions of ratios together in order to simultaneously take intoaccount different aspects.

This can be done by computing a composite indicator.

Complex variables can be measured by means of composite indicators. The basic

idea is to break down a complex variable into components which are measurable

by means of simple (partial) indicators. The partial indicators are then combined to

obtain the composite indicator. To this end one should

∗The paper has been written by and the proposed methods are due to M. Marozzi. L. Santa-

maria gave helpful comments to present the application results.

M. Corazza et al. (eds.), Mathematical and Statistical Methodsfor Actuarial Sciencesand Finance
© Springer-Verlag Italia 2010