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Linking the Value Assessment of Oil and Gas Firms to Ambidexterity Theory Using a Mixture of Normal Distributions

机译:利用正态分布的混合将石油和天然气企业的价值评估与双元性理论联系起来

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摘要

Oil and gas exploration and production firms have return profiles that are not easily explained by current financial theory – the variation in their market returns is non-Gaussian. In this paper, the nature and underlying reason for these significant deviations from expected behavior are considered. Understanding these differences in financial market behavior is important for a wide range of reasons, including: assessing investments, investor relations, decisions to raise capital, assessment of firm and management performance. We show that using a “thicker tailed” mixture of two normal distributions offers a significantly more accurate model than the traditionally Gaussian approach in describing the behavior of the value of oil and gas firms. This mixture of normal distribution is also more effective in bridging the gap between management theory and practice without the need to introduce complex time-sensitive GARCH and/or jump diffusion dynamics. The mixture distribution is consistent with ambidexterity theory that suggests firms operate in two distinct states driven by the primary focus of the firm: an exploration state with high uncertainty and, an exploitation (or production) state with lower uncertainty. The findings have direct implications on improving the accuracy of real option pricing techniques and futures analysis of risk management. Traditional options pricing models assume that commercial returns from these assets are described by a normal random walk. However, a normal random walk model discounts the possibility of large changes to the marketplace from events such as the discovery of important reserves or the introduction of new technology. The mixture distribution proves to be well suited to inherently describe the unusually large risks and opportunities associated with oil and gas production and exploration. A significance testing study of 554 oil and gas exploration and production firms empirically supports using a mixture distribution grounded in ambidexterity theory to describe the value fluctuations for these firms.
机译:石油和天然气勘探与生产公司的收益状况很难用当前的金融理论来解释-他们的市场收益变化是非高斯的。在本文中,考虑了这些与预期行为的重大偏离的性质和根本原因。出于多种原因,了解金融市场行为中的这些差异非常重要,包括:评估投资,投资者关系,筹集资金的决策,评估公司和管理绩效。我们表明,在描述石油和天然气公司的价值行为时,使用两个正态分布的“粗尾”混合提供了比传统的高斯方法更为准确的模型。正态分布的这种混合还可以更有效地弥合管理理论与实践之间的鸿沟,而无需引入复杂的时间敏感型GARCH和/或跳跃扩散动力学。混合分布与歧义理论相一致,歧义理论表明公司在公司主要关注点的驱动下处于两种不同的状态:具有高不确定性的探索状态和具有较低不确定性的开发(或生产)状态。这些发现对提高实物期权定价技术的准确性和风险管理的期货分析具有直接的意义。传统的期权定价模型假设这些资产的商业收益是通过正常的随机游走来描述的。但是,正常的随机游走模型使诸如发现重要储备或引入新技术等事件导致市场发生较大变化的可能性降低了。事实证明,混合物的分布非常适合固有地描述与油气生产和勘探相关的异常大的风险和机遇。 554家油气勘探和生产公司的显着性测试研究在经验上支持使用基于歧义性理论的混合分布来描述这些公司的价值波动。

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