Generating and Optimizing Human-Readable Quantitative Program Trading Strategies through a Genetic Programming Framework
Bin Teng, Yufeng Shi, Xin Wang, Yunchuan Sun · Procedia Computer Science · 2021
In this paper, we provide a highly flexible genetic programming framework for automatic generation and optimization of program trading strategies. We propose the input/output modules and their implementation methods, decoupled from the GP kernel, making it a priori-posteriori framework for trading practitioners. For human-readable purposes, we also give various empirical regularization methods, including NSGA-II multi-objective selection, as well as experimentally effective performance measures.