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 financial analysts). Moreover, the proposed method is always readily comprehended and requires milder assumptions.
A Simple Dimension Reduction Procedure for Corporate Finance Composite Indicators
MAROZZI, Marco;
2010
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 financial analysts). Moreover, the proposed method is always readily comprehended and requires milder assumptions.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
