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Robust Risk Estimation and Hedging: A Reverse Stress Testing Approach
Year Of Publication: 2013
Month Of Publication: April
Pages: 27
Download Count: 28
View Count: 1003
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 5-19-2013
Publisher: Administrator
Summary
Traditional risk modeling using Value-at-Risk (VaR) is widely viewed as ill equipped for dealing with tail risks. As a result, scenario-based portfolio stress testing is increasingly being promoted as central to the risk management process. A recent innovation in portfolio stress testing endorsed by regulators, called reverse stress testing, is intended to identify economic scenarios that will threaten a financial firm’s viability, but do so without injecting the manager’s cognitive biases into stress scenario specification. While the idea is intuitively appealing, no template has been provided to operationalize the idea. Some first steps in developing reverse stress testing approaches have begun to appear in the literature. Complexity and computational intensity appear to be important issues. A more subtle issue appearing in this emerging research is the relationship among the concepts of likelihood, plausibility, and representativeness. In this paper, we propose a novel method for reverse stress testing. The process starts with a multivariate normal distribution and uses Principal Components Analysis (PCA) along with Gram-Sch
Author(s)
Schachter, Barry Sign in to follow this author
Satchkov, Daniel Sign in to follow this author
Novosyolov, Arcady Sign in to follow this author
Kopeliovich, Yaacov Sign in to follow this author
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