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Nonparametric approach to rank global petroleum business opportunities

机译:非参数方法对全球石油商业机会进行排名

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Crude oil continues to be one of the significant energy sources. Several countries do not have enough indigenous oil and gas resources. These countries resort to overseas business of Exploration and Production (E&P) of oil to secure a stable supply. Profitability, risk and growth guide overseas investment decisions. Selection of overseas investment opportunities are critical for a firm because of uncertainty in identifying and quantifying the attendant geological, commercial, social and political risks as well as return on investment. To secure overseas oil acreage, business entities intend to invest in overseas E&P destination having reasonable petroleum reserve, favorable contract terms (fiscal terms), well-developed infrastructure, sound legal system, minimum country risk (CR) (economic, social and political) and facilitate relative ease to do business in that country. The countries have varied mix of these parameters, and it leads to growing concern to screen and rank overseas investment opportunities. Methodologies to rank global opportunities should take into consideration the risk factors such as petroleum potential, infrastructure, geo-political scenario, contract terms, etc. We coin the term for the numerical rank as Globalization Index (GI), which is a function of the factors considered to affect the decision of a business entity in screening the global destinations for venturing in to E&P business of crude oil. This paper is an attempt to model these factors by invoking Alternating Conditional Expectation methodology to find GI.
机译:原油仍然是重要的能源之一。一些国家没有足够的本地石油和天然气资源。这些国家依靠石油的勘探与生产(E&P)海外业务来确保稳定的供应。盈利能力,风险和增长指导着海外投资决策。选择海外投资机会对公司至关重要,因为在确定和量化伴随的地质,商业,社会和政治风险以及投资回报方面存在不确定性。为了确保海外石油种植面积,企业实体打算在具有合理石油储备,优惠合同条款(财政条款),发达的基础设施,完善的法律制度,最低国家风险(CR)(经济,社会和政治)的海外E&P目的地进行投资并促进相对容易地在该国开展业务。各国对这些参数的组合各不相同,因此越来越引起人们对筛选和排名海外投资机会的关注。对全球机遇进行排名的方法应考虑到诸如石油潜力,基础设施,地缘政治情景,合同条款等风险因素。我们将数字排名的术语称为全球化指数(GI),这是全球机遇的函数。在筛选全球企业从事原油勘探与生产业务的目的地时,被认为会影响企业实体决策的因素。本文试图通过调用交替条件期望方法来查找GI来对这些因素进行建模。

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