METHODS FOR ANALYSIS OF FINANCIAL DATA AND DEVELOPMENT OF ALGORITHMIC STRATEGIES FOR AUTOMATED TRADING

Abstract

Automatic trading software speeds up the process of trading on foreign exchange market. Automated trading software allows monitoring a large number of parameters and make decisions in real time. Software trading methods reduce the impact of human emotions in decision making process and allow to overcome problems that may arise due to lack of concentration. Modern technology, software, and real-time information does not guaranty successful trading results. Technology provides more information and a faster process of trading, however, for successful trading results is still necessary to find an appropriate approach how to use of available information and how to make correct decisions. This paper describes the application of neural networks, data mining and evolutionary methods for the analysis of financial data and search for profitable trading strategies.