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摘要翻译：
阶乘矩是粒子物理中描述相空间分辨率($\δ$)较小时多重数分布的方便工具。它们包括粒子系统中的所有关联，并表示这些粒子之间任何关联的整体特征。在这封信中，我们展示了高能物理和定量金融结果之间的直接比较。对于物理和金融，我们都说明了当分辨率变得足够小时，粒子之间的关联会导致多重数分布的展宽和动力学涨落。从阶乘矩的母函数出发，对正负号返回序列的间隙概率进行了预测。缺口被定义为负收益后连续正收益的数量，因此这是负收益的缺口。相反，正回报的缺口。然后，空隙概率在空隙大小内呈指数抑制。我们用数据证实了这一预测。
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英文标题：
《Factorial Moments in Complex Systems》
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作者：
Laurent Schoeffel (CEA - Saclay)
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最新提交年份：
2011
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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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英文摘要：
Factorial moments are convenient tools in particle physics to characterize the multiplicity distributions when phase-space resolution ($\Delta$) becomes small. They include all correlations within the system of particles and represent integral characteristics of any correlation between these particles. In this letter, we show a direct comparison between high energy physics and quantitative finance results. Both for physics and finance, we illustrate that correlations between particles lead to a broadening of the multiplicity distribution and to dynamical fluctuations when the resolution becomes small enough. From the generating function of factorial moments, we make a prediction on the gap probability for sequences of returns of positive or negative signs. The gap is defined as the number of consecutive positive returns after a negative return, thus this is a gap in negative return. Inversely for a gap in positive return. Then, the gap probability is shown to be exponentially suppressed within the gap size. We confirm this prediction with data.
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PDF链接：
https://arxiv.org/pdf/1108.5946
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