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

机译:从默认概率到信用差价: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:Moody的KMV等信用风险模型现已在市场上成熟,并为个人公司提供债券管理者可靠的默认概率。到目前为止,它一直很难将这些概率联系起来对公司债券市场观察到的实际信用差价。通过[1]和[2]偏离高斯行为的金融市场中的扩大法律的存在,我们开发了一种定量将这些违约概率联系起来的信贷差价(市场价格)的模型。本研究的主要输入数量仅仅是行业产量数据的不同时间与穆迪的KMV的成熟和预期默认频率(EDF)。本文的经验结果清楚地表明,该模型可用于计算来自EDF的近似信用差价(市场价格),独立于成熟的时间和所考虑的行业部门。此外,该模型在样品外设置方面是有效的,它会在欧洲债券市场上产生一致的结果,其中数据稀缺,可以充分用于近似于企业水平的信贷差价。

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