Academic research in accounting has focused its interest mainly in quantitative data from financial statements, financial indices, and statistical data. However, technology and information systems have evolved and as a result the processing of qualitative data (texts, reports, and news) can offer valuable information and solve a variety of problems in business environment and in academic research.

In this research, there is an attempt to investigate the contribution of textual analysis methods in earnings, liquidity, and cash flow forecasting. Tone, and complexity of financial reports may offer to managers important insights about the future performance of the company.

This study examines these features of the company’s reports by using algorithmic methods and algorithmic indices to detect success drivers of the company. The combination of textual data processing and fundamental analysis could possibly bridge the information gap between investors and managers. This research examines the contribution of textual analysis in the interpretation of quantitative data in the accounting disclosures.