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首页> 外文期刊>The quarterly review of economics and finance >Are Copula-GoF-tests of any practical use? Empirical evidence for stocks,commodities and FX futures
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Are Copula-GoF-tests of any practical use? Empirical evidence for stocks,commodities and FX futures

机译：Copula-GoF测试有实际用途吗？股票，商品和外汇期货的经验证据

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In this paper, the optimality of bivariate copula-VaR models and the usefulness of several goodness-of-fit tests for copulas are analysed in a comprehensive empirical study using data for stocks, commodities and FX futures. In particular, I try to answer two questions: (1) which parametric copula is optimal for estimating the VaR and Expected Shortfall (ES) of a given portfolio consisting of linear assets? (2) How can the VaR- or ES-optimal parametric copula be identified in-sample? To answer these questions, the VaR and ES for a total of 12,000 bivariate portfolios are estimated from 435 linear assets over eight different time windows. The results show that although copula-models with GARCH-margins yield considerably better VaR-estimates than correlation-based models, the identification of the optimal parametric copula form is a serious unsolved problem. The analysis of three state-of-the-art approaches for testing a copula-model's goodness-of-fit showed that none of the tests is able to identify the optimal parametric form unequivocally. In addition to this result, for more than 80% of all portfolios considered, all five parametric copula models yielded worse ES-estimates than the correlation-based benchmark or underestimated actual portfolio risk. Moreover, the backtesting results show that the optimal parametric copula is both dependent on the risk measure and time-variant.
机译：在本文中，使用股票，商品和外汇期货的数据，在全面的实证研究中分析了双变量copula-VaR模型的最优性以及copula的几种拟合优度检验的有用性。特别是，我尝试回答两个问题：（1）哪种参数对数最适合估计由线性资产组成的给定投资组合的VaR和预期缺口（ES）？ （2）如何在样本中识别VaR或ES最佳参数系？为了回答这些问题，在八个不同的时间范围内，从435个线性资产中估算出总计12,000个二元投资组合的VaR和ES。结果表明，尽管具有GARCH裕度的copula模型比​​基于相关的模型产生的VaR估计要好得多，但是最佳参数copula形式的识别却是一个严重的未解决问题。对三种用于测试copula模型的拟合优度的最新方法的分析表明，没有一种测试能够明确地确定最佳参数形式。除此结果外，对于考虑的所有投资组合中的80％以上，与基于相关性的基准相比，所有五个参数组合copula模型产生的ES评估均较差，或者实际投资风险被低估了。此外，回测结果表明，最佳参数对数取决于风险度量和时变。

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