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A Structural Approach for Predicting Default Correlation 预测违约相关性的结构方法
Pub Date : 2012-08-31 DOI: 10.2139/ssrn.2140257
Sheen X. Liu, H. Qi, Jian Shi, Y. Xie
Default correlation is a critical concept in risk management for fixed income investment, bank management, and insurance industry, working capital management, among many. We extend the Leland-Toft term structure model into a two-firm environment and predict the default correlation between two firms by directly simulating the calibrate model based on the observed equity data (1990-2010) for various ratings. Using our empirical default correlation estimation as the benchmark, our investigation sheds more light on the structural approach in predicting default correlation. The results show that our approach outperforms the previous Zhou’s model, thereby our approach is not only theoretical improvement, but also has an empirical advantage.
违约相关性是固定收益投资、银行管理、保险行业、营运资金管理等风险管理中的一个重要概念。我们将Leland-Toft期限结构模型扩展到两家公司的环境中,并通过基于观察到的股票数据(1990-2010)直接模拟校准模型来预测两家公司之间的默认相关性。利用我们的经验违约相关性估计作为基准,我们的研究更多地揭示了预测违约相关性的结构方法。结果表明,我们的方法优于之前的Zhou的模型,因此我们的方法不仅是理论上的改进,而且具有实证优势。
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Structural Bond Pricing Models
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