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A New Default Probability Calculation Formula and Its Application under Uncertain Environments

机译:一个新的默认概率计算公式及其在不确定环境下的应用

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In the real world, corporate defaults will be affected by both external market shocks and counterparty risks.With this in mind, we propose a new default intensitymodel with counterparty risks based on both external shocks and the internal contagion effect.The effects of the external shocks and internal contagion on a company cannot, however, be observed, as uncertainty in the real world contains both randomness and fuzziness.This prevents us from determining the size of the shocks accurately. In this study, fuzzy set theory is utilized to study a looping default credit default swap (CDS) pricing model under uncertain environments. Following this, we develop a new fuzzy formpricing formula for CDS, the simulation analysis of which shows that all kinds of fuzziness in the market have a significant impact on credit spreads, and that the credit spreads, relative to the degree of external shock fuzziness, are much more sensitive.Nevertheless, for a certain degree of fuzziness in themarket, credit spreads, relative to changes in counterparty risk, are much more sensitive. Using random analysis and fuzzy numbers, one can think of even more uncertain sources at play than the processes of looping default and investor subjective judgment on the financial markets, and this broadens the scope of possible credit spreads. Compared to the existing related literature, our new fuzzy form CDS pricing model with counterparty risk can consider more factors that influence default and is closer to the reality of the complexity of the dynamics of default. It can also employ the membership function to describe the fuzzy phenomenon, enable the fuzzy phenomenon to be estimated in two kinds of state, and can simultaneously reflect both the fuzziness and randomness in financial markets.
机译:在现实世界中,企业违约将受到外部市场冲击和交易对手风险的影响。在这方面,我们提出了一种基于外部冲击和内部传染效应的对抗对手风险的新的违约强度模型。外部冲击的影响然而,在公司的内部传染不能被观察到,因为现实世界中的不确定性含有随机性和模糊性。这可以防止我们准确地确定冲击的大小。在本研究中,利用模糊集理论在不确定环境下研究循环默认信用默认交换(CDS)定价模型。在此之后,我们开发了一种新的CD模糊形式化公式,其模拟分析表明,市场上各种模糊对信贷差异产生了重大影响,并且信用差价相对于外部冲击模糊程度,更敏感。无论如何,对于Outmarket的一定程度的模糊,相对于交易对手风险的变化,信贷传播更为敏感。使用随机分析和模糊数字,可以考虑比循环违约和投资者主观判断的流程更不确定的来源,这扩大了可能的信贷差价范围。与现有相关文献相比,我们的新模糊形式CDS定价模型具有交易对手风险,可以考虑更多影响默认的因素,并且更接近默认动态的复杂性的现实。它还可以采用会员函数来描述模糊现象,使得在两种状态下估计模糊现象,并且可以同时反映金融市场中的模糊和随机性。

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