Applying genetic algorithms with speciation for optimization of grid template pattern detection in financial markets

作者：

Highlights：

• Using a fixed size grid of weights increases the accuracy of pattern detection.

• Deciding market exiting prices using volatility increases detection effectiveness.

• Overlapping candlesticks with grids helps mitigating false positives detection.

• Trading algorithms with more available information increase their efficiency.

摘要

•Using a fixed size grid of weights increases the accuracy of pattern detection.•Deciding market exiting prices using volatility increases detection effectiveness.•Overlapping candlesticks with grids helps mitigating false positives detection.•Trading algorithms with more available information increase their efficiency.

论文关键词：Genetic algorithm,Speciation,Pattern discovery,Grid of weights,Optimization,Financial markets

论文评审过程：Received 2 April 2019, Revised 20 December 2019, Accepted 6 January 2020, Available online 17 January 2020, Version of Record 24 January 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113191