英文标题：
《Statistical inference of co-movements of stocks during a financial
  crisis》
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作者：
Takero Ibuki, Shunsuke Higano, Sei Suzuki, Jun-ichi Inoue and Anirban
  Chakraborti
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最新提交年份：
2013
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英文摘要：
  In order to figure out and to forecast the emergence phenomena of social systems, we propose several probabilistic models for the analysis of financial markets, especially around a crisis. We first attempt to visualize the collective behaviour of markets during a financial crisis through cross-correlations between typical Japanese daily stocks by making use of multi- dimensional scaling. We find that all the two-dimensional points (stocks) shrink into a single small region when a economic crisis takes place. By using the properties of cross-correlations in financial markets especially during a crisis, we next propose a theoretical framework to predict several time-series simultaneously. Our model system is basically described by a variant of the multi-layered Ising model with random fields as non-stationary time series. Hyper-parameters appearing in the probabilistic model are estimated by means of minimizing the \'cumulative error\' in the past market history. The justification and validity of our approaches are numerically examined for several empirical data sets.
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中文摘要：
为了弄清和预测社会系统的出现现象，我们提出了几种分析金融市场的概率模型，尤其是在危机前后。我们首先试图通过利用多维标度，通过典型日本日股之间的相互关联，来可视化金融危机期间市场的集体行为。我们发现，当经济危机发生时，所有的二维点（股票）收缩成一个小区域。通过利用金融市场，尤其是在危机期间的相互关联特性，我们接下来提出了一个同时预测多个时间序列的理论框架。我们的模型系统基本上由多层伊辛模型的变体描述，随机场为非平稳时间序列。概率模型中出现的超参数是通过最小化过去市场历史中的“累积误差”来估计的。我们的方法的合理性和有效性通过几个经验数据集进行了数值检验。
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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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