Abstract
Price variation is complex in the market. Expectation transformation plays a key role in the variation process. Incomplete and imperfect information are involved in the process forming expectation transformation. This paper tries to identify expectation transformation under different exogenous conditions in a housing market through an agent-based simulation approach. Firstly, this paper constructs basic model elements according to empirical sense and theoretical findings. Secondly, this paper builds an intelligence-and-trading behaviour model of agents based on genetic programming (GP) approach. The agent-based housing market testbed (ABHMT) is constructed. To verify the model, this paper sets two groups of control experiments. Through the experiments, we reveal five new findings in the field. The control experiments show the effectiveness of ABHMT. The comparison of real-life history scenarios and the simulation results shows the validity of the model. With the help of ABHMT, it is possible to simulate reality-alike situations to assist more market analyses for a certain application case.
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