摘要翻译：
需求和供给不确定下的能源市场均衡模型引起了人们的广泛关注。本文利用两阶段随机均衡模型对新冠肺炎疫情下的原油市场份额进行了建模。我们用随机变量来描述需求和供给中的不确定性，并提供了两种类型的生产决策（此时此地和等待观望）。第一阶段的此时决定不取决于未来随机事件的结果，第二阶段的观望决定允许取决于未来随机事件，并在罕见的意外情况下调整此时决定的可行性，如新冠肺炎疫情期间观察到的情况。我们发展了一个快速算法来求两阶段随机均衡的解。我们利用2019年1月至2020年5月的真实市场数据，展示了预测石油市场份额的两阶段随机均衡模型的鲁棒性。
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英文标题：
《Equilibrium Oil Market Share under the COVID-19 Pandemic》
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作者：
Xiaojun Chen, Yun Shi, Xiaozhou Wang
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最新提交年份：
2020
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分类信息：

一级分类：Mathematics        数学
二级分类：Optimization and Control        优化与控制
分类描述：Operations research, linear programming, control theory, systems theory, optimal control, game theory
运筹学，线性规划，控制论，系统论，最优控制，博弈论
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一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
  Equilibrium models for energy markets under uncertain demand and supply have attracted considerable attentions. This paper focuses on modelling crude oil market share under the COVID-19 pandemic using two-stage stochastic equilibrium. We describe the uncertainties in the demand and supply by random variables and provide two types of production decisions (here-and-now and wait-and-see). The here-and-now decision in the first stage does not depend on the outcome of random events to be revealed in the future and the wait-and-see decision in the second stage is allowed to depend on the random events in the future and adjust the feasibility of the here-and-now decision in rare unexpected scenarios such as those observed during the COVID-19 pandemic. We develop a fast algorithm to find a solution of the two-stage stochastic equilibrium. We show the robustness of the two-stage stochastic equilibrium model for forecasting the oil market share using the real market data from January 2019 to May 2020.
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PDF链接：
https://arxiv.org/pdf/2007.15265