Uncertainty, especially surrounding U.S. presidential elections, has been known to affect global financial markets. One key driver of this uncertainty is trade policy uncertainty, which has seen increased volatility in recent years due to political agendas such as the “America First” policy. Due to the U.S being an important trading partner to Sweden, it is interesting to investigate if there's a spillover effect on the Swedish market from American policies. Therefore, the purpose of this thesis is to investigate whether the U.S. Trade Policy Uncertainty (TPU) Index can predict excess stock returns in the Swedish market, with a focus on election periods. Using a time series study and ordinary least squares (OLS) regressions, we analyze monthly data from 2005 to 2025 across the OMXS-30 index and seven major Swedish sectors. To evaluate forecasting power, we compare model performance against a historical average benchmark using root mean squared error (RMSE) in out-of-sample periods. The results show that the TPU-Index does not consistently predict excess returns. However, during certain election periods, particularly when global shocks are absent, the TPU model outperforms the benchmark in several sectors. Notably, all sectors demonstrate improved forecast accuracy relative to the benchmark in the 2020 election cycle despite all industries failing to show significance individually due to the Lagrange multiplier test. Our findings shows that, during stable market conditions, the TPU-Index can be used to forecast Swedish stock excess returns, with lower RMSE than the benchmark, indicating that the TPU-Index contains information not captured by traditional benchmarks and is therefore contradicting the semi-strong form of the EMH. While not statistically significant at all times, it still offers great practical value for investors and policy makers that want an alternative tool to predict future excess returns relative to the classical average benchmark.