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Measuring and Managing Risk with Random Limit Normal Distribution
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TitleMeasuring and Managing Risk with Random Limit Normal Distribution  
AuthorGong Xiaolin (Caelyn),Chen Zengjing,Zhang Xiaopu and Yang Shuzhen  
OrganizationShandong University;China Banking Regulatory Commission 
Emailgcaelyn@gmail.com; 
Key WordsRisk Models; Prudential Risk Management; High Peak and Fat Tails; Value at Risk; Expected Shortfall 
AbstractThe 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 NumberWP691 
Time2014-09-09 
  • Institute of Economics, Chinese Academy of Social Sciences
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