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Utility‐based shortfall risk: Efficient computations via Monte Carlo
Author(s) -
Hu Zhaolin,
Zhang Dali
Publication year - 2018
Publication title -
naval research logistics (nrl)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 68
eISSN - 1520-6750
pISSN - 0894-069X
DOI - 10.1002/nav.21814
Subject(s) - expected shortfall , monte carlo method , computer science , computation , mathematical optimization , risk management , sensitivity (control systems) , focus (optics) , econometrics , value at risk , risk analysis (engineering) , mathematics , economics , finance , algorithm , statistics , engineering , medicine , physics , optics , electronic engineering
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.