股票投资组合的 Copula 中心不对称性
Copula Central Asymmetry of Equity Portfolios
AI总结：
本文提出基于经验 Copula 与生存 Copula 的 Cramér-von Mises 距离及 tie-break bootstrap 的非参数检验方法，用于检测投资组合收益的 Copula 中心不对称性，并发现该不对称性随时间变化，在规模组合及市场下行期更为显著。
摘要：
金融危机通常伴随着资产收益之间横截面依赖性的增强，导致收益分布的下尾与上尾之间出现不对称。如今，检测不对称依赖被认为是市场监管、风险管理和投资组合配置中的关键环节。本文提出一种非参数检验程序，用于检验 Copula 中心对称性假设，该程序基于经验 Copula 与其生存对应物之间的 Cramér-von Mises 距离，并在平稳时间序列的标准假设下推导了该检验的渐近性质。本文使用功能强大的 tie-break bootstrap 方法，所附模拟研究表明，该方法能够在多达 25 个序列、观测数量相当于一年日收益数据的情况下检测出不对称性。将该程序分别应用于各年度的美国投资组合收益后发现，Copula 中心不对称的程度随时间变化，且在近期表现较弱。不对称性在基于规模的投资组合中更为显著，而在基于账面市值比和动量的投资组合中则相对较弱。在基于行业分类的投资组合中，不对称性在市场下行期间出现，这与金融传染的叙述相一致。
英文摘要：
Financial crises are usually associated with increased cross-sectional dependence between asset returns, causing asymmetry between the lower and upper tail of return distribution. The detection of asymmetric dependence is now understood to be essential for market supervision, risk management, and portfolio allocation. I propose a non-parametric test procedure for the hypothesis of copula central symmetry based on the Cramér-von Mises distance of the empirical copula and its survival counterpart, deriving the asymptotic properties of the test under standard assumptions for stationary time series. I use the powerful tie-break bootstrap that, as the included simulation study implies, allows me to detect asymmetries with up to 25 series and the number of observations corresponding to one year of daily returns. Applying the procedure to US portfolio returns separately for each year shows that the amount of copula central asymmetry is time-varying and less present in the recent past. Asymmetry is more critical in portfolios based on size and less in portfolios based on book-to-market and momentum. In portfolios based on industry classification, asymmetry is present during market downturns, coherently with the financial contagion narrative.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
