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From Default Probabilities to Credit Spreads: Credit Risk Models Explain Market Prices

机译:从违约概率到信用利差:信用风险模型解释市场价格

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Credit risk models like Moody's KMV are now well established in the market and give bond managers reliable default probabilities for individual firms. Until now it has been hard to relate those probabilities to the actual credit spreads observed on the market for corporate bonds. Inspired by the existence of scaling laws in financial markets by [1] and [2] deviating from the Gaussian behavior, we develop a model that quantitatively links those default probabilities to credit spreads (market prices). The main input quantities to this study are merely industry yield data of different times to maturity and expected default frequencies (EDFs) of Moody's KMV. The empirical results of this paper clearly indicate that the model can be used to calculate approximate credit spreads (market prices) from EDFs, independent of the time to maturity and the industry sector under consideration. Moreover, the model is effective in an out-of-sample setting, it produces consistent results on the European bond market where data are scarce and can be adequately used to approximate credit spreads on the corporate level.
机译:穆迪(Moody)的KMV等信用风险模型现已在市场中确立,并为债券管理人提供了针对个别公司的可靠违约概率。到目前为止,很难将这些概率与公司债券市场上观察到的实际信用息差相关联。受[1]和[2]偏离高斯行为的金融市场规模定律的启发,我们开发了一个模型,该模型将那些违约概率与信用利差(市场价格)定量地联系在一起。这项研究的主要输入量仅仅是穆迪KMV到期日和预期违约频率(EDF)不同时期的行业收益数据。本文的经验结果清楚地表明,该模型可用于计算EDF的近似信用价差(市场价格),与到期时间和所考虑的行业无关。此外,该模型在样本外设置中非常有效,它在欧洲债券市场上产生一致的结果,在欧洲债券市场上,数据很少,可以充分用来估算公司一级的信用利差。

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