英文标题：
《Irreversibility of financial time series: a graph-theoretical approach》
---
作者：
Lucas Lacasa, Ryan Flanagan
---
最新提交年份：
2016
---
英文摘要：
  The relation between time series irreversibility and entropy production has been recently investigated in thermodynamic systems operating away from equilibrium. In this work we explore this concept in the context of financial time series. We make use of visibility algorithms to quantify in graph-theoretical terms time irreversibility of 35 financial indices evolving over the period 1998-2012. We show that this metric is complementary to standard measures based on volatility and exploit it to both classify periods of financial stress and to rank companies accordingly. We then validate this approach by finding that a projection in principal components space of financial years based on time irreversibility features clusters together periods of financial stress from stable periods. Relations between irreversibility, efficiency and predictability are briefly discussed.
---
中文摘要：
在远离平衡运行的热力学系统中，时间序列不可逆性和熵产生之间的关系最近得到了研究。在这项工作中，我们将在金融时间序列的背景下探讨这一概念。我们利用可见度算法以图论的形式量化了1998-2012年期间演变的35个金融指数的时间不可逆性。我们表明，这一指标是对基于波动性的标准衡量标准的补充，并利用它对财务压力时期进行分类，并据此对公司进行排名。然后，我们通过发现基于时间不可逆性的财务年度主成分空间预测将稳定期的财务压力期聚集在一起，从而验证了这种方法。简要讨论了不可逆性、效率和可预测性之间的关系。
---
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
--
一级分类：Physics        物理学
二级分类：Data Analysis, Statistics and Probability        数据分析、统计与概率
分类描述：Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
物理数据分析的方法、软硬件：数据处理与存储；测量方法；统计和数学方面，如参数化和不确定性。
--

---
PDF下载：
-->