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Using Dynamic Copulae for Modeling Dependency in Currency Denominations of a Diversified World Stock Index

机译:使用动态Copulae对多种世界股票指数的货币面额依存关系建模

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The aim of this paper is to model the dependency among log-returns when security account prices are expressed in units of a well diversified world stock index. The dependency in log-returns of cur-rency denominations of the index is modeled using time-varying copulae, aiming to identify the best fitting copula family. The Student-t copula turns generally out to be superior to e.g. the Gaussian copula, where the dependence structure relates to the multivariate normal distribution. It is shown that merely changing the distributional assumption for the log-returns of the marginals from normal to Student-t leads to a significantly better fit. The Student-t copula with Student-t marginals is able to better capture dependent extreme values than the other models considered. Furthermore, the paper applies copulae to the estimation of the Value-at-Risk and the expected shortfall of a portfolio con-structed of savings accounts of different currencies. The proposed copula-based approach allows to split market risk into general and specific market risk, as defined in regulatory documents. The paper demonstrates that the approach performs clearly better than the RiskMetrics approach, a widely used methodology for Value-at-Risk estimation.
机译:本文的目的是对当安全账户价格以高度多样化的世界股票指数的单位表示时对数回报之间的依赖性进行建模。使用时变的copulae对指数的货币面额的对数收益率进行建模,以找出最合适的copula族。 Student-t copula通常被证明优于例如高斯系,依赖关系与多元正态分布有关。结果表明,仅将边际对数回归的分布假设从正态分布更改为学生t分布,就可以显着提高拟合度。带有Student-t边际的Student-t copula能够比其他模型更好地捕获相关的极值。此外,本文将copulae应用于风险价值的估计以及由不同货币的储蓄账户构成的投资组合的预期缺口。提议的基于copula的方法允许将市场风险分为监管文件中定义的一般和特定市场风险。本文表明,该方法的性能明显优于RiskMetrics方法,RiskMetrics方法是一种广泛使用的风险价值估算方法。

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