The year 2000 has been very difficult for the
Greek stock market, which has suffered from
stagnation both in terms of share prices and
liquidity. This fact, along with the recent
pervasive record of false financial
statements, increased the interest of the
authorities, stock market, Ministry of the
Economy and the banking sector in early warning
systems. In this context, the absence
of a Greek study on the subject is striking.
This paper intends to address this need in the
existing literature. For this purpose,
univariate and multivariate statistical tools
were employed to investigate the usefulness
of publicly available variables for detecting
FFS. A total of ten variables were found to be
possible indicators of FFS. These include the
ratios: debt to equity, sales to total assets, net
profit to sales, accounts receivable to sales,
net profit to total assets, working capital to
total assets, gross profit to total assets,
inventory to sales, total debt to total assets,
and financial distress (Z-score). Using
stepwise logistic regression, two models were
developed with a high probability of
detecting FFS in a sample. The models
include the variables: the inventories to sales
ratio, the ratio of total debt to total assets, the
working capital to total assets ratio, the net
profit to total assets ratio, and financial
distress (Z-score).