基于概率统计不确定性模型的CCA方法

Prudential risk management and adapted CCA approach based on probability model with ambiguity

文章旨在优化与完善未定权益分析(CCA)这一重要宏、微观金融风险度量与监管模型,以期助益于我国风险管理技术的储备与创新,促进审慎风险监管理论、方法和实践的发展.利用我国随机分析与计算领域的国际领先成果,将CCA方法进益至对经济学发展具有重要意义的“不确定性”假设条件下更为敏锐、审慎、更适合我国金融市场发展现状的风险计量与分析模型.同时,通过纳入漂移率风险因素,拓展了经典CCA方法的风险监控覆盖范围.

The paper is to improve the famous contingent claims analysis(CCA)approach.It first demonstrates that the core assumption of Merton-CCA model is unrealistic and is not apt to measure risk in a realistic,dynamic economic environment.Then,a probability model with ambiguity,which incorporates model uncertainty,volatility uncertainty and mean uncertainty,is proven to be more effective for measuring and managing risk in the real business world.Based on the recent progress in stochastic analysis and calculus,the paper proposes a G-CCA model,a more risk sensitive,thus a more prudential risk measurement model,especially in emerging financial markets.Moreover,adding to all the valuable advantages of the Merton-CCA model,the new model extends the risks covered by traditional CCA models by taking into account risks arising from the uncertainty of expected asset returns.