Stress Testing Engineering: The Real Risk Measurement?

Guégan, Dominique; Hassani, Bertrand K.

doi:10.1007/978-3-319-07524-2_3

Cited by 1 publication

(1 citation statement)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…• In a situation such as depicted by a stress-testing process with forward looking perspective, if the risks are not correctly measured then the foundations will be very fragile and the outcome of the exercise not reliable. Indeed, stressing a situation requires an appropriate initial assessment of the real exposure, otherwise the stress would merely model what should have been captured originally and therefore be useless (Bensoussan et al (2015), Guégan and Hassani (2015b), Hassani (2015)).…”

Section: Conclusion and Recommendationsmentioning

confidence: 99%

Risk or Regulatory Capital? Bringing Distributions Back in the Foreground

Guégan

Hassani

2015

SSRN Journal

View full text Add to dashboard Cite

T his paper discusses the regulatory requirem ent (B asel C om m ittee, E C B -SSM and E B A ) to m easure financial institutions' m ajor risks, for instance M arket, Credit and O perational, regarding the choice of the risk m easures, the choice of the distribution s used to m odel them and the level of confidence. W e highlight and illustrate the paradoxes and the issues observed im plem enting an approach over another and the inconsistencies betw een the m ethodologies suggested and the goal to achieve. T his paper m akes som e recom m endations to the supervisor and proposes alternative procedures to m easure the risks. AbstractThis paper discusses the regulatory requirement (Basel Committee, ECB-SSM and EBA) to measure financial institutions' major risks, for instance Market, Credit and Operational, regarding the choice of the risk measures, the choice of the distributions used to model them and the level of confidence. We highlight and illustrate the paradoxes and the issues observed implementing an approach over another and the inconsistencies between the methodologies suggested and the goal to achieve. This paper make some recommendations to the supervisor and proposes alternative procedures to measure the risks. 2 Disclaimer: The opinions, ideas and approaches expressed or presented are those of the authors and do not necessarily reflect Santander's position. As a result, Santander cannot be held responsible for them.2 This paper has been written in a very particular period of time as most regulatory papers written in the past 20 years are currently being questioned by both practitioners and regulators themselves. Some distress or disarray has been observed among risk managers as most models required by the regulation were not consistent with their own objective of risk management. The enlightenment brought by this paper is based on an academic analysis of the issues engendered by some pieces of regulation and it has not for purpose to create any sort of polemic. 1 6 For a given p in [0, 1], ÷ the V aR (1≠p)% , and X a random variable which represents losses during a prespecified period (such as a day, a week, or some other chosen time period) then, ES (1≠p)% = E(X|X > ÷).(1.2)

show abstract

Section: Conclusion and Recommendationsmentioning

confidence: 99%