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摘要翻译：
金融市场为研究拥挤环境下的决策提供了一个理想的框架。数据的数量和准确性都允许应用来自物理学的工具和概念，这些工具和概念研究集体和突现现象或自组织和高度异构的系统。我们分析了29，930个非专家个人的活动，他们占整个市场交易量的一小部分。个体非常异构的活动遵循Zipf定律，而同步网络属性揭示了一个社区结构。因此，我们将个人活动与金融市场中最显著的宏观信号即波动性联系起来，并量化了个人如何因波动性而明显两极分化。我们的同步网络属性的多样性也表明，个体关注的是波动性，而不是直接相互模仿，从而为人类活动中的羊群现象提供了有趣的解释。这些结果还可以改进基于Agent的模型，因为它们提供了Agent参数的直接估计。
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英文标题：
《Volatility polarization of non-specialized investors' heterogeneous
activity》
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作者：
Mario Guti\'errez-Roig and Josep Perell\'o
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最新提交年份：
2013
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分类信息：
一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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英文摘要：
Financial markets provide an ideal frame for studying decision making in crowded environments. Both the amount and accuracy of the data allows to apply tools and concepts coming from physics that studies collective and emergent phenomena or self-organised and highly heterogeneous systems. We analyse the activity of 29,930 non-expert individuals that represent a small portion of the whole market trading volume. The very heterogeneous activity of individuals obeys a Zipf's law, while synchronization network properties unveil a community structure. We thus correlate individual activity with the most eminent macroscopic signal in financial markets, that is volatility, and quantify how individuals are clearly polarized by volatility. The assortativity by attributes of our synchronization networks also indicates that individuals look at the volatility rather than imitate directly each other thus providing an interesting interpretation of herding phenomena in human activity. The results can also improve agent-based models since they provide direct estimation of the agent's parameters.
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PDF链接：
https://arxiv.org/pdf/1302.3169
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