Portfolio managers, auditors and financial analysts process accounting data and financial time series of companies to determine their economic heath. Volatility in stock prices is formed in a significant proportion by accounting statements, the managerial quality in the companies and the trends in the markets. The extended amount of accounting data and the complexity of financial indices demand advanced methods of econometrics and artificial intelligence to provide the hidden information to analysts, managers and investors. Hybrid systems of neural networks with genetic algorithms optimization are able to support efficiently decisions on portfolio management, corporate management, and financial accounting. Principle Components Analysis with a Neural Network and Genetic Algorithms optimizations provides acceptable results of corporate financial classification.