Abstract: This paper proposes a method to evolving parameter sets for Risk-Based（RB） bidding strategy in CDA（Continuous Double Auction） market by using the Particle Swarm Optimization algorithm.The strategy involves the agent forming a bid or asks by assessing the degree of risk involved and making a prediction about the competitive equilibrium price that is likely to be reached in the marketplace.However，there are some parameters setting that significantly influences on the trader’s behaviors and the market efficiency.This experiment results show the evolutionary RB bidding strategy can rapidly adapt to the market circumstance contrasted to the original RB bidding strategy.