In financial investment planning,a large number of components that interact in varying and complexways are involved.This leads to complex behavior that is difficult to understand,predict and manage.Asingle intelligent technique can not solve the complicated and elaborate investment planning problems.Itis necessary to study those problems synthetically by combining the multiple intelligent techniques.Weemployed fussy algorithms,genetic algorithms,etc.to solve complicated financial portfolio managementin this paper.We analyse and design an agent-based hybrid intelligent system by following the methodolo-gy for constructing agent-based hybrid intelligent system(MAHIS).The system starts with the financialrisk tolerance evaluation based on fussy algorithms.Asset allocation,portfolio selections,interest predic-tions,and ordered weighted averaging can be conducted by using hybrid intelligent techniques.The plan-ning agent in the system can easily access all the intelligent processing agents,including the agents of fi-nancial risk tolerance assessment,asset allocation,portfolio selection,interest prediction,and decisionaggregation.Overall system robustness is facilitated. In financial investment planning, a large number of components that interact in varying and complexways are involved. This leads to complex behavior that is difficult to understand, predict and manage. Asingle intelligent technique can not solve the complicated and elaborate investment planning problems. to study those problems synthetically by combining the multiple intelligent techniques. Whaseloyed fussy algorithms, genetic algorithms, etc.to solve complicated financial portfolio management in this paper. We analyze and design an agent-based hybrid intelligent system by following the methodolo-gy for constructing agent -based hybrid intelligent system (MAHIS). The system starts with the financialrisk tolerance based on fussy algorithms. Asset allocation, portfolio selections, interest predictions, and ordered weighted averaging can be conducted by using hybrid intelligent techniques. The plan-ning agent in the system can easily access all the intelligent processing agents, i ncluding the agents of fi-nancial risk tolerance assessment, asset allocation, portfolio selection, interest prediction, and decisionaggregation. Overall system robustness is facilitated.