从Black-Scholes的角度来看,选举前的联盟协议
D Mitrović1,2
1Faculty of Mathematics, University of Vienna, Oskar Morgenstern Platz-1, 1090, Vienna, Austria. darko.mitrovic@univie.ac.at.
Scientific reports
|February 9, 2024
概括
这项研究使用随机过程建模政党支持,类似于金融选项. 它确定了少数政党在联盟中获得代表的必要选民支持,使用黑山.
科学领域:
- 政治科学 政治科学是指政治学.
- 数学建模的数学建模
- 随机过程 随机过程
背景情况:
- 政党价值与公司价值相似,由选民支持驱动.
- 选民支持动态可以被建模为一个随机过程,受决定性增长和随机波动 (白噪声) 的影响.
- 这与金融期权定价模型相似,股票价格遵循类似的随机行为.
研究的目的:
- 确定一个合理的选民支持门,以使一个小政党在联盟中获得代表.
- 将选项定价类比应用于政治学,特别是针对联盟组建和选举成功.
- 分析最近的黑山选举 (2023年6月) 作为这些联盟动态的案例研究.
主要方法:
- 利用随机过程建模,特别是维纳过程,来表示选民支持动态.
- 与期权定价理论进行并行绘制,以分析联盟情景.
- 将模型应用于2023年6月黑山选举的经验数据.
主要成果:
- 该研究为计算少数党代表所需的联盟支持水平建立了一个框架.
- 对黑山选举的分析为模型的实际应用提供了洞察力.
- 确定特定的支持水平,使小党能够获得额外的代表.
结论:
- 随机建模方法为理解选举联盟动态提供了一种新方法.
- 调查结果为选举中的战略联盟规划提供了定量基础.
- 该案例研究表明,该模型在复杂的选举环境中具有多个政治参与者的相关性.
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