标题： 基于Copula的金融时间序列证据积累聚类 显示英文标题

标题： Copula-Based Clustering of Financial Time Series via Evidence Accumulation

摘要： 理解资产收益的依赖结构在风险评估中是基础性的，并且在投资组合分散策略中尤为重要。我们提出了一种聚类方法，其中通过经典层次化程序和多种基于copula的差异度量来实现多种分类中的证据积累。被分组在同一簇中的资产，在风险情景下的随机行为是相似的，风险厌恶的投资者可以利用这些信息来构建风险分散的投资组合。通过使用 EURO STOXX 50 指数的数据，对该策略进行了实证演示。 显示英文摘要

摘要： Understanding the dependence structure of asset returns is fundamental in risk assessment and is particularly relevant in a portfolio diversification strategy. We propose a clustering approach where evidence accumulated in a multiplicity of classifications is achieved using classical hierarchical procedures and multiple copula-based dissimilarity measures. Assets that are grouped in the same cluster are such that their stochastic behavior is similar during risky scenarios, and riskaverse investors could exploit this information to build a risk-diversified portfolio. An empirical demonstration of such a strategy is presented by using data from the EURO STOXX 50 index.