Long tail uncertainty distributions in novel risk probability classification

O. Schwabe, E. Shehab, J. Erkoyuncu

Research output: Contribution to conferencePaper

3 Citations (Scopus)

Abstract

Successful engineering, manufacturing, supply and service of advanced aerospace products benefits from the effective capture, predication and reduction of risk probability. Based on the analysis of the risk probability of 15,624 group wide largely unrelated enterprise risk management entries at Rolls-Royce plc., an aerospace manufacturing and service company, non-random patterns of probability in approx. 70% of aggregated risk profiles were identified, whereby approx. 40% of these exhibit long tail (leptokurtic) characteristics. Future research is recommended to identify relevant parametric risk probability variable (relationships) and to determine whether risk probability can be predicated.
Original languageEnglish
Number of pages6
DOIs
Publication statusPublished - 2015

Fingerprint

Uncertainty
Long tail
Manufacturing
Aerospace
Enterprise risk management

Keywords

  • Black-swan
  • Long-tail
  • Probability
  • Risk

Cite this

Long tail uncertainty distributions in novel risk probability classification. / Schwabe, O.; Shehab, E.; Erkoyuncu, J.

2015.

Research output: Contribution to conferencePaper

@conference{38fbec527825418195fcd1b3312b541f,
title = "Long tail uncertainty distributions in novel risk probability classification",
abstract = "Successful engineering, manufacturing, supply and service of advanced aerospace products benefits from the effective capture, predication and reduction of risk probability. Based on the analysis of the risk probability of 15,624 group wide largely unrelated enterprise risk management entries at Rolls-Royce plc., an aerospace manufacturing and service company, non-random patterns of probability in approx. 70{\%} of aggregated risk profiles were identified, whereby approx. 40{\%} of these exhibit long tail (leptokurtic) characteristics. Future research is recommended to identify relevant parametric risk probability variable (relationships) and to determine whether risk probability can be predicated.",
keywords = "Black-swan, Long-tail, Probability, Risk",
author = "O. Schwabe and E. Shehab and J. Erkoyuncu",
year = "2015",
doi = "10.1016/j.procir.2015.04.033",
language = "English",

}

TY - CONF

T1 - Long tail uncertainty distributions in novel risk probability classification

AU - Schwabe, O.

AU - Shehab, E.

AU - Erkoyuncu, J.

PY - 2015

Y1 - 2015

N2 - Successful engineering, manufacturing, supply and service of advanced aerospace products benefits from the effective capture, predication and reduction of risk probability. Based on the analysis of the risk probability of 15,624 group wide largely unrelated enterprise risk management entries at Rolls-Royce plc., an aerospace manufacturing and service company, non-random patterns of probability in approx. 70% of aggregated risk profiles were identified, whereby approx. 40% of these exhibit long tail (leptokurtic) characteristics. Future research is recommended to identify relevant parametric risk probability variable (relationships) and to determine whether risk probability can be predicated.

AB - Successful engineering, manufacturing, supply and service of advanced aerospace products benefits from the effective capture, predication and reduction of risk probability. Based on the analysis of the risk probability of 15,624 group wide largely unrelated enterprise risk management entries at Rolls-Royce plc., an aerospace manufacturing and service company, non-random patterns of probability in approx. 70% of aggregated risk profiles were identified, whereby approx. 40% of these exhibit long tail (leptokurtic) characteristics. Future research is recommended to identify relevant parametric risk probability variable (relationships) and to determine whether risk probability can be predicated.

KW - Black-swan

KW - Long-tail

KW - Probability

KW - Risk

UR - http://www.mendeley.com/research/long-tail-uncertainty-distributions-novel-risk-probability-classification

UR - http://www.mendeley.com/research/long-tail-uncertainty-distributions-novel-risk-probability-classification

U2 - 10.1016/j.procir.2015.04.033

DO - 10.1016/j.procir.2015.04.033

M3 - Paper

ER -