Biological brain-inspired genetic complementary learning for stock market and bank failure prediction

Genetic complementary learning (GCL) is a biological brain-inspired learning system based on human pattern recognition, and genes selection process. It is a confluence of the hippocampal complementary learning and the evolutionary genetic algorithm. With genetic algorithm providing the possibility of optimal solution, and complementary learning providing the efficient pattern recognition, GCL may offer superior performance. In contrast to other computational finance tools such as neural network and statistical methods, GCL provides greater interpretability and it does not rely on the assumption of the underlying data distribution. It is an evolving and autonomous system that avoids the time-consuming process of manual rule construction or modeling. This is highly favorable especially in financial world where data is ever changing, and requires frequent update. The feasibility of GCL as stock market predictor, and bank failure early warning system is investigated. The experimental results show that GCL is a competent computational finance tools for stock market prediction and bank failure early warning system.