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Forecasting Chinese Corporate Bond Defaults: Comparative Study of Market- vs. Accounting-Based Models

机译:预测中国公司债券违约:基于市场模型与基于会计模型的比较研究

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摘要

This paper provides the first empirical study on bond defaults in the Chinese market. It overcomes the deficiencies of existing methods, which suffer from lack of actual default data for back testing. With newly available bond default data, we analyze the roles of market variables against accounting variables under various models. While we find that Merton's market-based structural model and KMV's Distance to Default exhibit languid discriminating power compared with hazard models that have carefully constructed predictors, other market variables carry significant information about bond defaults and could help improve on models with only the accounting variables. This implies that the collective intelligence of the market could somehow mitigate the distortion caused by misreported accounting information. Further, model performance can be significantly improved by adding predicting variables that link an individual financial measure to the broader market performance, such as the relative margin�a business environment proxy introduced in this study. We not only shed light on the default behavior of the Chinese bond market, but also provide a promising approach to improve the variable selection process.
机译:本文提供了关于中国市场债券违约的第一项实证研究。它克服了现有方法的缺陷,这些缺陷缺少用于回测的实际默认数据。利用最新可用的债券违约数据,我们在各种模型下针对会计变量分析了市场变量的作用。尽管我们发现默顿的基于市场的结构模型和KMV的``违约距离''与精心构建了预测变量的风险模型相比表现出较弱的歧视力,但其他市场变量携带了有关债券违约的重要信息,并且可以帮助改进仅包含会计变量的模型。这意味着市场的集体智慧可以以某种方式减轻因误报会计信息而导致的失真。此外,可以通过添加将单个财务指标与更广泛的市场绩效联系起来的预测变量来显着改善模型绩效,例如本研究中引入的相对利润率。我们不仅揭示了中国债券市场的违约行为,而且还提供了一种有前途的方法来改善变量选择过程。

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