A study of agricultural futures market simulation based on SBL model

We propose an agent-based model of a futures market to analyze the characters of wheat futures markets price stylized facts. We use the Brenner's “stochastic belief learning model” to describe the speculative agents' beliefs learning process. In this model, the bounded speculative agents have different learning capability and risk aversion degree, and they can learn both from individual and others' experiences. New market price is generated though a sealed-bid auction clearance mechanism. The simulation can reproduce the important observed stylized facts in futures markets price time series. Our results show futures price volatility has close relation with large speculators' trading. Noise traders' survival in the market depend on the external information flow generating process and others behaviors.

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