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A statistics‐based approach for crude oil supply risk assessment
Author(s) -
Hassani Hossein,
Danesh Mohammad Ali,
Javan Afshin,
Pospiech Ryszard,
Odulaja Adedapo
Publication year - 2017
Publication title -
opec energy review
Language(s) - English
Resource type - Journals
eISSN - 1753-0237
pISSN - 1753-0229
DOI - 10.1111/opec.12101
Subject(s) - monte carlo method , oil supply , crude oil , econometrics , statistics , supply and demand , set (abstract data type) , distribution (mathematics) , economics , computer science , mathematics , petroleum engineering , engineering , microeconomics , mathematical analysis , programming language
This paper presents two approaches towards quantifying short‐term crude oil supply uncertainty. It provides some background information on the oil market and discusses different methods used in forecasting supply. Both approaches—semiquantitative ( SQ ) and Monte Carlo ( MC )—are based on a risk matrix with likelihood and severity scores assigned. The result of the SQ approach is a risk band presented in percentage terms, whereas the MC method yields a probability distribution. The differences, advantages and disadvantages, as well as the potential expansions of both approaches are discussed. Both methods are applied to a set of major non‐ OPEC oil producing countries, and the obtained results are compared.