MAHIS-based analysis and design of financial investment planning system

In financial investment planning, a large number of components that interact in varying and complex ways are involved. This leads to complex behavior that is difficult to understand, predict and manage. A single intelligent technique can not solve the complicated and elaborate investment planning problems. It is necessary to study those problems synthetically by combining the multiple intelligent techniques. We employed fussy algorithms, genetic algorithms, etc. to solve complicated financial portfolio management in this paper. We analyse and design an agent-based hybrid intelligent system by following the methodology for constructing agent-based hybrid intelligent system (MAHIS). The system starts with the financial risk tolerance evaluation based on fussy algorithms. Asset allocation, portfolio selections, interest predictions, and ordered weighted averaging can be conducted by using hybrid intelligent techniques. The planning agent in the system can easily access all the intelligent processing agents, including the agents of financial risk tolerance assessment, asset allocation, portfolio selection, interest prediction, and decision aggregation. Overall system robustness is facilitated.