英文标题：
《Agent-based model with asymmetric trading and herding for complex
  financial systems》
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作者：
Jun-jie Chen, Bo Zheng, Lei Tan
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最新提交年份：
2014
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英文摘要：
  Background: For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results.   Methods: To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors\' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data.   Results: With the model parameters determined for six representative stock-market indices in the world respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities.   Conclusions: We reveal that for the leverage and anti-leverage effects, both the investors\' asymmetric trading and herding are essential generation mechanisms. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries.
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中文摘要：
背景：对于复杂的金融系统，负和正收益波动率相关性，即所谓的杠杆效应和反杠杆效应，对于理解价格动态尤为重要。然而，杠杆效应和反杠杆效应的微观起源仍然不清楚，如何在基于代理的建模中产生这些效应仍然是个未知数。另一方面，在构建微观模型时，从经验数据而不是结果的统计拟合来确定模型参数是一个很有前途的概念。方法：为了研究金融系统中收益-波动相关性的微观起源，我们考虑了真实市场中投资者的个人和集体行为，并构建了一个基于代理的模型。代理人之间相互联系，分组交易，特别是引入了两种新的微观机制，即投资者的不对称交易和牛市和熊市中的羊群效应。此外，我们还提出了根据历史市场数据确定模型中关键参数的有效方法。结果：分别对世界上六种具有代表性的股票市场指数确定了模型参数，通过模拟得到了相应的杠杆效应或反杠杆效应，其影响幅度和持续时间与实证结果一致。同时，我们的模型产生了真实市场的其他特征，如收益率的厚尾分布和波动率的长期相关性。结论：我们发现，对于杠杆效应和反杠杆效应，投资者的不对称交易和羊群效应都是重要的生成机制。这两种微观机制和关键参数的确定方法可应用于具有类似不对称性的其他复杂系统。
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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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一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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