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首页> 外文期刊>The North American journal of economics and finance >Modeling non-normal corporate bond yield spreads by copula
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Modeling non-normal corporate bond yield spreads by copula

机译：建模非正常公司债券收益率由Copula蔓延

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摘要

This research focuses on modeling for how corporate bond yield spreads are affected by explanatory variables such as equity volatility, interest rate volatility, r, slope, rating, liquidity, coupon rate, and maturity. The existing literature assumes normality and linearity in the analysis, which is not the case in our sample. Thus, through a powerful and flexible copula approach, we study the dependence at the mean of the joint distribution by using the Gaussian copula marginal regression method and the dependence structure at the tails by using various copula functions. To our knowledge, this is the first application of the copula marginal regression model to bond market data. In addition, we employ several copula functions to test for the tail dependence between yield spreads and other explanatory variables. We find stronger tail dependence in the joint upper tail for the relation between equity volatility and yield spreads, among others. This result indicates the positive effect of equity volatility on yield spreads in the upper tail is greater than that in the low tail. This finding should be useful to practitioners, such as investors. By relying on better-fitting, more meaningful statistical models, this paper contributes to the extant literature on how corporate bond yield spreads are determined.
机译：本研究重点介绍了企业债券收益率差异的建模，这些分析受解释性变量的影响，如公平波动，利率波动，R，坡度，评级，流动性，优惠券和成熟度。现有文献假设分析中的正常性和线性，这不是我们的样本中的情况。因此，通过强大且灵活的Copula方法，我们通过使用各种Copula功能来研究通过使用高斯Copula边缘回归方法和尾部处的依赖结构来研究联合分布的平均值。据我们所知，这是Copula边缘回归模型的第一次应用于债券市场数据。此外，我们采用了几个Copula功能来测试产量扩散和其他解释变量之间的尾部依赖性。我们在联合上部尾部中发现了更强烈的尾部依赖，以实现股权波动性与产量蔓延的关系。该结果表明公平挥发性对上部尾部的产量扩散的积极效果大于低尾部的产量。这一发现对于从业者，例如投资者。通过依靠更好的拟合，更有意义的统计模型，本文有助于确定企业债券收益率差价如何的现存文献。

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