A computing approach to agent bidding in continuous double auction

Abstract

The real-world continuous double auction CDA market is a dynamic environment. However, most of the existing agent bidding strategies are simply designed for static markets. A new detecting method for bidding strategy is necessary for more practical simulations and applications. In this paper, we present a novel agent-based computing approach called the GDX Plus GDXP model. In the proposed model, trades are decided according to the market events in history combined with the forecast of market trends. The GDXP model employs a dynamic adjustment mechanism to make the bidding strategy adapt to the shocks in a dynamic environment. The experimental results of the comparison between GDXP and other typical models, with respect to both static and dynamic CDA markets, demonstrate the performance of the GDXP model.