A meta-grammatical evolutionary process for portfolio selection and trading

作者：Contreras Ivan; Ignacio Hidalgo J; Nuez Letamendia Laura; Manuel Velasco J

来源：Genetic Programming and Evolvable Machines, 2017, 18(4): 411-431.

DOI：10.1007/s10710-017-9304-1

• Grammatical evolution
• Automated trading systems
• Meta-GE
• Technical analysis
• Fundamental analysis
• Macroeconomic analysis

This study presents the implementation of an automated trading system that uses three critical analyses to determine time-decisions and portfolios for investment. The approach is based on a meta-grammatical evolution methodology that combines technical, fundamental and macroeconomic analysis on a hybrid top-down paradigm. First, the method provides a low-risk portfolio by analyzing countries and industries. Next, aiming to focus on the most robust companies, the system filters the portfolio by analyzing their economic variables. Finally, the system analyzes prices and volumes to optimize investment decisions during a given period. System validation involves a series of experiments in the European financial markets, which are reflected with a data set of over nine hundred companies. The final solutions have been compared with static strategies and other evolutionary implementations and the results show the effectiveness of the proposal.

• 出版日期2017-12