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Investors face the problem of how to effectively trade and manage risk under political uncertainty. The goal of this Capstone project was to develop a methodological framework through which trading strategies for an uncertain political event can be identified. Looking at the past four United States presidential elections, the Capstone team evaluated shocks on equity markets caused by U.S. presidential elections. In order to understand the elections’ economic impact, situational narratives were constructed based on the relationship between the two major political parties in the United States (Democratic and Republican) and four sectorial Exchange Traded Funds (ETFs) that the study examined: Defense, finance, pharmaceuticals and fossil fuels.

It became apparent that the market mirrors government spending behavior and regulatory changes. Hence, the economic impact on chosen ETFs differ in direction and magnitude between a Democratic or Republican President elect. The study followed a three-fold approach: first, the Capstone team developed a probability model to predict future elections based on a regression analysis with two variables, incumbency and approval rating. Second, the team determined spikes in self-constructed ETFs with an event study. Third, the team performed scenarios and sensitivity analysis of outcomes using a Monte Carlo Simulation. Finally, based on the results of the empirical analysis, investment strategies were developed: the probability model informed who is going to win the election. Depending on Republican or Democrat, a different directional change in sectorial ETFs is expected, which ultimately creates trading opportunities.