摘要翻译：
在湍流和金融市场等复杂系统中，长时滞和短时滞的动力学分别由高斯统计量和厚尾统计量表示，需要统一的描述。为了解决这个问题，我们分析了一个真实的数据集，即价格波动，在广泛的时间尺度上包含了这两种制度。利用经验时间序列的Kramers-Moyal(KM)系数，得到了价格收益概率密度函数(PDF)的演化方程。对于时间尺度相关方程，我们也给出了一致的渐近解。从这些解决方案中，新的关系连接PDF特征，如尾指数，与KM系数的参数。结果揭示了从高斯统计到肥尾统计的动力学路径，为观察到类似交叉的其他复杂系统提供了见解。
---
英文标题：
《From short to fat tails in financial markets: A unified description》
---
作者：
A.A.G. Cortines, R. Riera, C. Anteneodo
---
最新提交年份：
2008
---
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：Statistical Mechanics        统计力学
分类描述：Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变，热力学，场论，非平衡现象，重整化群和标度，可积模型，湍流
--
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。
--

---
英文摘要：
  In complex systems such as turbulent flows and financial markets, the dynamics in long and short time-lags, signaled by Gaussian and fat-tailed statistics, respectively, calls for a unified description. To address this issue we analyze a real dataset, namely, price fluctuations, in a wide range of temporal scales to embrace both regimes. By means of Kramers-Moyal (KM) coefficients evaluated from empirical time series, we obtain the evolution equation for the probability density function (PDF) of price returns. We also present consistent asymptotic solutions for the timescale dependent equation that emerges from the empirical analysis. From these solutions, new relationships connecting PDF characteristics, such as tail exponents, to parameters of KM coefficients arise. The results reveal a dynamical path that leads from Gaussian to fat-tailed statistics, furnishing insights on other complex systems where akin crossover is observed.
---
PDF链接：
https://arxiv.org/pdf/0801.3263