英文标题：
《Predictable markets? A news-driven model of the stock market》
---
作者：
Maxim Gusev, Dimitri Kroujiline, Boris Govorkov, Sergey V. Sharov,
  Dmitry Ushanov and Maxim Zhilyaev
---
最新提交年份：
2014
---
英文摘要：
  We attempt to explain stock market dynamics in terms of the interaction among three variables: market price, investor opinion and information flow. We propose a framework for such interaction and apply it to build a model of stock market dynamics which we study both empirically and theoretically. We demonstrate that this model replicates observed market behavior on all relevant timescales (from days to years) reasonably well. Using the model, we obtain and discuss a number of results that pose implications for current market theory and offer potential practical applications.
---
中文摘要：
我们试图从三个变量之间的相互作用来解释股市动态：市场价格、投资者意见和信息流。我们为这种互动提出了一个框架，并将其应用于建立一个股票市场动力学模型，我们对该模型进行了实证和理论研究。我们证明，该模型在所有相关时间尺度（从几天到几年）上相当好地复制了观察到的市场行为。利用该模型，我们获得并讨论了一些结果，这些结果对当前的市场理论具有启示，并提供了潜在的实际应用。
---
分类信息：

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
--
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。
--

---
PDF下载：
-->