@inproceedings{1d1493278bf44b48a073ab5441ea0346,
title = "Stochastic beliefs learning and commodity futures price dynamics",
abstract = "We propose a multi-agent-based artificial futures market to understand commodity futures price dynamics, which is called stylized facts. The multi-agent-based artificial futures market includes hedger agents and speculative agents. We use Brenner's stochastic belief learning model (SBL) to describe speculative agents' learning process. The SBL is a social learning process with local information. New market price is generated though a sealed-bid auction clearance mechanism. Our simulation result can reproduce the important observed stylized facts of futures price. The simulation programming language is Matlab 7. Our results show clustered volatility depends on speculator agents' imitations which are caused by social learning process. Using this simulation model, we can find futures price volatility has close relation with large speculator agents' trading activity.",
keywords = "Clustered volatility, Futures price, Heterogeneous agent, Stochastic belief learning",
author = "Tan Li and Qi, \{Zhong Ying\} and Niu, \{Hong Yuan\}",
year = "2010",
doi = "10.1109/ICMSE.2010.5719945",
language = "英语",
isbn = "9781424481163",
series = "2010 International Conference on Management Science and Engineering, ICMSE 2010",
pages = "1186--1191",
booktitle = "2010 International Conference on Management Science and Engineering, ICMSE 2010",
note = "17th International Conference on Management Science and Engineering, ICMSE 2010 ; Conference date: 24-11-2010 Through 26-11-2010",
}