英文标题：
《A Three-state Opinion Formation Model for Financial Markets》
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作者：
Bernardo J. Zubillaga and Andr\\\'e L. M. Vilela and Chao Wang and
  Kenric P. Nelson and H. Eugene Stanley
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最新提交年份：
2019
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英文摘要：
  We propose a three-state microscopic opinion formation model for the purpose of simulating the dynamics of financial markets. In order to mimic the heterogeneous composition of the mass of investors in a market, the agent-based model considers two different types of traders: noise traders and contrarians. Agents are represented as nodes in a network of interactions and they can assume any of three distinct possible states (e.g. buy, sell or remain inactive). The time evolution of the state of an agent is dictated by probabilistic dynamics that include both local and global influences. A noise trader is subject to local interactions, tending to assume the majority state of its nearest neighbors, whilst a contrarian is subject to a global interaction with the behavior of the market as a whole, tending to assume the state of the global minority of the market. The model exhibits the typical qualitative and quantitative features of real financial time series, including distributions of returns with heavy tails, volatility clustering and long-time memory for the absolute values of the returns. The distributions of returns are fitted by means of coupled Gaussian distributions, quantitatively revealing transitions between leptokurtic, mesokurtic and platykurtic regimes in terms of a non-linear statistical coupling which describes the complexity of the system.
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中文摘要：
为了模拟金融市场的动态，我们提出了一个三态微观意见形成模型。为了模拟市场中大量投资者的异质构成，基于代理的模型考虑了两种不同类型的交易者：噪音交易者和反向交易者。代理被表示为交互网络中的节点，它们可以假设三种不同的可能状态中的任何一种（例如购买、出售或保持不活动）。agent状态的时间演化由概率动力学决定，其中包括局部和全局影响。噪音交易者受制于局部互动，倾向于假设其最近邻居的多数状态，而反向交易者受制于与整个市场行为的全球互动，倾向于假设市场的全球少数状态。该模型展示了真实金融时间序列的典型定性和定量特征，包括厚尾收益率分布、波动率聚类和收益绝对值的长时间记忆。收益分布通过耦合高斯分布进行拟合，定量揭示了在描述系统复杂性的非线性统计耦合方面，轻轨、中库尔特和平轨制度之间的过渡。
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分类信息：

一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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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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