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arXiv 1002.0917q-fin.TRphysics.soc-phq-fin.ST
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连续双向拍卖市场中基于主体模型的统计性质

Statistical properties of agent-based models in markets with continuous double auction mechanism

Jie-Jun Tseng, Chih-Hao Lin, Chih-Ting Lin, Sun-Chong Wang, Sai-Ping Li

摘要:

真实世界的市场显示幂律特征的变量,如股票价格波动。为了进一步了解市场行为,我们在基于网络的预测市场平台上进行了一系列市场实验,这使我们能够重建交易者之间的交易网络。从这些网络中,我们能够记录交易者的程度,交易者社区的规模,交易者之间的交易时间间隔以及其他感兴趣的变量。所有这些变量的分布都表现出幂律行为。另一方面,基于主体的模型已经被提出来研究真实金融市场的性质。我们在这里研究这些基于代理的模型的统计特性,并将它们与我们基于网络的市场实验的结果进行比较。在这项工作中,三个基于Agent的模型,即零智能(ZI),零智能加(ZIP)和Gjerstad-Dickhaut(GD)进行了研究。基于这三个代理模型的变量进行了计算机模拟。我们发现,虽然是最天真的基于代理的模型,ZI确实最好地描述了在现实市场中观察到的属性。我们的研究表明,从现实世界的市场中产生所观察到的属性的基本成分实际上可能是一个不断演变的动力系统的结果,其基本特征类似于ZI模型。

英文摘要:

Real world markets display power-law features in variables such as price fluctuations in stocks. To further understand market behavior, we have conducted a series of market experiments on our web-based prediction market platform which allows us to reconstruct transaction networks among traders. From these networks, we are able to record the degree of a trader, the size of a community of traders, the transaction time interval among traders and other variables that are of interest. The distributions of all these variables show power-law behavior. On the other hand, agent-based models have been proposed to study the properties of real financial markets. We here study the statistical properties of these agent-based models and compare them with the results from our web-based market experiments. In this work, three agent-based models are studied, namely, zero-intelligence (ZI), zero-intelligence-plus (ZIP) and Gjerstad-Dickhaut (GD). Computer simulations of variables based on these three agent-based models were carried out. We found that although being the most naive agent-based model, ZI indeed best describes the properties observed in real markets. Our study suggests that the basic ingredient to produce the observed properties from real world markets could in fact be the result of a continuously evolving dynamical system with basic features similar to the ZI model.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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