[论文解读] The Price of Political Uncertainty: Evidence from the 2016 U.S. Presidential Election and the U.S. Stock Markets
本文采用事件研究法,考察2016年美国总统大选期间政治不确定性对行业股票收益的影响。研究发现,尽管市场最初对特朗普意外胜选作出负面反应,但次日异常收益转为正值,且不确定信息假说(UIH)未获支持——相反,市场对各行业的反应因预期政策变化而异。
There is bountiful evidence that political uncertainty stemming from presidential elections or doubt about the direction of future policy make financial markets significantly volatile, especially in proximity to close elections or elections that may prompt radical policy changes. Although several studies have examined the association between presidential elections and stock returns, very little attention has been given to the impacts of elections and election induced uncertainty on stock markets. This paper explores, at sectoral level, the uncertain information hypothesis (UIH) as a means of explaining the reaction of markets to the arrival of unanticipated information. This hypothesis postulates that political uncertainty is greater prior to the elections (relative to pre-election period) but is resolved once the outcome of the elections is determined (relative to post-election period). To this end, we adopt an event-study methodology that examines abnormal return behavior around the election date. We show that collapsing stock returns around the election result is reversed by positive abnormal return on the next day, except some cases where we note negative responses following the vote count. Although Trump's win plunges US into uncertain future, positive reactions of abnormal return are found. Therefore, our results do not support the UIH hypothesis. Besides, the effect of political uncertainty is sector-specific. While some sectors emerged winners (healthcare, oil and gas, real estate, defense, financials and consumer goods and services), others took the opposite route (technology and utilities). The winning industries are generally those that will benefit from the new administration's focus on rebuilding infrastructure, renegotiating trade agreements, reforming tax policy and labour laws, increasing defense funding, easing restrictions on energy production, and rolling back Obamacare.
研究动机与目标
- 调查2016年美国总统大选期间的政治不确定性对美国股市行业层面收益的影响。
- 检验不确定信息假说(UIH),该假说认为市场波动性在选举前达到峰值,结果公布后趋于下降。
- 评估出人意料的选举结果,特别是特朗普的胜选,是否导致各行业中异常股票收益出现可预测的模式。
- 识别在新政府政策纲领预期下,哪些行业受益或受损。
- 为金融市场上政治风险定价在重大民主事件中的表现提供实证证据。
提出的方法
- 以美国总统大选日(2016年11月8日)为中心,采用事件研究法构建事件窗口。
- 通过市场模型对每个行业每日股票收益与市场指数收益进行回归,计算异常收益。
- 分析事件窗口内5个交易日(选举日前后各两天)的异常收益,以捕捉市场反应。
- 将分析按10个主要行业细分,评估同一政治冲击下不同市场的反应差异。
- 使用Fama-French三因子模型作为基准,控制收益估计中的规模、价值和市场风险因素。
- 通过比较选举前、选举日和选举后各阶段的波动率与收益模式,检验UIH。
实验结果
研究问题
- RQ12016年美国总统大选的政治不确定性如何影响不同行业的异常股票收益?
- RQ2不确定信息假说(UIH)是否成立,即选举前波动率上升,结果公布后不确定性是否下降?
- RQ3特朗普意外胜选是否引发可预测的市场反应,且该反应是否在次日出现反转?
- RQ4哪些行业在选举后出现正或负的异常收益,其背后的政策预期如何解释这些模式?
- RQ5政治不确定性在多大程度上被反映在行业股票收益中,且这种影响在各行业中是否对称?
主要发现
- 在选举结果公布前,异常收益转为负值,表明市场已将不确定性定价,但结果公布次日转为正值,显示收益出现反转。
- 不确定信息假说(UIH)未获支持,市场在选举后未表现出持续的不确定性下降;相反,观察到收益出现反转。
- 医疗保健、石油与天然气、房地产、国防、金融以及消费品与服务等行业录得正向异常收益,可能源于预期的基础设施支出、税制改革和监管放松。
- 科技与公用事业行业出现负向异常收益,可能因对创新激励减弱和监管放松的担忧。
- 异常收益的幅度在各行业间存在显著差异,表明政治不确定性对不同行业的影响因政策暴露程度而异。
- 选举次日异常收益的反转表明,尽管最初出现恐慌,市场仍迅速消化了特朗普意外胜选带来的冲击。
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