Predicting the Financial Status of Companies Using Content Analysis the Reports of the Board of Directors

Severe economic fluctuations and adverse consequences for investors. The need for predictive models has made corporate finance necessary. In this regard, This research is intended by examining the relationship between financial ratios and the content of the board's reports open a new way to predict company status. For this purpose, were extracted frequency of words and phrases with positive and negative semantic load using the word extraction algorithm, From the text of the board's reports 219 non helpless companies and 81 helpless companies. Results of regression estimation positive and negative words ratio on financial performance indicators, shows in companies with financial health, negative words have a significant relationship with functional criteria. Evidence showed in these companies, managers are not trying to hide their financial crisis. The results for the helpless companies were different In general, there was no meaningful relationship between the words with the performance indicators of these companies. It looks like this group of companies by confusing the, they try to prevent to selling from their shares by stakeholders.