A statistics-based approach for crude oil supply risk assessment

摘要

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.