Affiliations: College of Computer Science and Technology, Jilin University, No. 2699, Qianjin street, Changchun, China | College of Computer Science and Technology, Changchun Normal University, No. 677, Changji street, Changchun, China
Note: [] Supported by National Natural Science Foundation of China under Grant Nos. 60603030, 60773099, 60703022, 60873149, 60973088, the National High-Tech Research and Development Plan of China under Grant No. 2006AA10Z245 and 2006AA10A309.
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.
