Optimization of technical indicators in real time with multiobjective evolutionary algorithms

摘要: Technical analysis uses technical indicators to identify changes in market trend. These are composed by a set of parameters and rules, whose values try determine the future movements assets. This paper addresses optimization these depending on current market, allowing better returns with less risk. The use Multi-objective Evolutionary Algorithms (MOEAs) is proposed this work obtain best parameter real time belonging collection that will help buying selling shares. Unlike other previous approaches, necessity repeating process each new data enters system justified, searching for adjustment every moment. technique can greatly improve results Buy & Hold (B H) strategy even operating daily. statement be demonstrated comparing those presented literature.