Measuring and Managing Risk with Random Limit Normal Distribution Read
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Title | Measuring and Managing Risk with Random Limit Normal Distribution
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Author | Gong Xiaolin (Caelyn),Chen Zengjing,Zhang Xiaopu and Yang Shuzhen |
Organization | Shandong University;China Banking Regulatory Commission |
Email | gcaelyn@gmail.com; |
Key Words | Risk Models; Prudential Risk Management; High Peak and Fat Tails; Value at Risk; Expected Shortfall |
Abstract | The paper introduces a new distribution to improve tail risk modelling. We first demonstrate that the fundamental model of risk metrics, like VaR and ES, leads to their inability to measure risk in a realistic, dynamic economic environment. Then, random limit normal distribution model is proven to be more effective for measuring and managing risk in the real business world. By employing the new distribution, we then propose more prudential risk metrics —— R-VaR and R-ES. |
Serial Number | WP691 |
Time | 2014-09-09 |
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