Utility‐based shortfall risk: Efficient computations via Monte Carlo

With the development of financial risk management, the notion of convex risk measures has been proposed and has gained increasing attentions. Utility‐based shortfall risk (SR), as a specific and important class of convex risk measures, has become popular in recent years. In this paper we focus on th...

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Bibliographic Details
Published in:Naval research logistics 2018-08, Vol.65 (5), p.378-392
Main Authors: Hu, Zhaolin, Zhang, Dali
Format: Article
Language:English
Subjects:
asymptotic normality
convex risk measure
Economic models
Financial management
Monte Carlo simulation
Optimization
Risk assessment
Risk management
sample average approximation
Sensitivity analysis
simulation
Statistical methods
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Summary:With the development of financial risk management, the notion of convex risk measures has been proposed and has gained increasing attentions. Utility‐based shortfall risk (SR), as a specific and important class of convex risk measures, has become popular in recent years. In this paper we focus on the computational aspects of SR, which are significantly understudied but fundamental for risk assessment and management. We discuss efficient estimation, optimization, and sensitivity analysis of SR, based on Monte Carlo techniques and stochastic optimization methods. We also conduct extensive numerical studies on the proposed approaches. The numerical results further demonstrate the effectiveness of these approaches.
ISSN:0894-069X
1520-6750
DOI:10.1002/nav.21814