论文标题
金融市场的简单持久性：过滤，生成过程和投资组合风险
Simplicial persistence of financial markets: filtering, generative processes and portfolio risk
论文作者
论文摘要
我们介绍了简单的持久性，这是随后的时间层中网络图案的时间演变的度量。我们观察到从相关过滤的结构演变中的长度记忆，在持续的简单复合物数量中，有两个制度的功率定律衰减。测试了基础时间序列的空模型，以研究生成过程的性质及其进化约束。网络是通过TMFG过滤技术和阈值生成的，表明基于嵌入的过滤方法（TMFG）能够在整个市场样本中识别高阶结构，而阈值方法失败。这些长期记忆过程的衰减指数用于根据其发展阶段和流动性来表征金融市场。我们发现，更多的液体市场往往会持续衰减。这与共同的理解形成鲜明对比，即发达市场更随机。我们发现，对于每个单个变量的动力学，它们确实是不可预测的，但是对于与变量的集体演变有关的是更可预测的。这可能意味着对系统性冲击的脆弱性更高。
We introduce simplicial persistence, a measure of time evolution of network motifs in subsequent temporal layers. We observe long memory in the evolution of structures from correlation filtering, with a two regime power law decay in the number of persistent simplicial complexes. Null models of the underlying time series are tested to investigate properties of the generative process and its evolutional constraints. Networks are generated with both TMFG filtering technique and thresholding showing that embedding-based filtering methods (TMFG) are able to identify higher order structures throughout the market sample, where thresholding methods fail. The decay exponents of these long memory processes are used to characterise financial markets based on their stage of development and liquidity. We find that more liquid markets tend to have a slower persistence decay. This is in contrast with the common understanding that developed markets are more random. We find that they are indeed less predictable for what concerns the dynamics of each single variable but they are more predictable for what concerns the collective evolution of the variables. This could imply higher fragility to systemic shocks.
