Date of Award

2026

Document Type

Thesis

Degree Name

Bachelor of Science

Department

Mathematical Economics

First Advisor

Dr. Maia Linask

Second Advisor

Dr. Lilla Orr

Abstract

To address gaps in existing research, this paper selects two U.S. government shutdown periods, 2018-2019 and 2025, as research samples to explore the effect of policy uncertainty on sentiment. This paper primarily analyzes the following two research questions.

First, what is the correlation between government shutdown-related sentiment during the shutdown period and daily market fluctuations? Specifically, can the sentiment index constructed from shutdown-related news effectively predict the next-day stock return during the event period?

Second, does the market have a learning effect? That is, between 2018-2019 and 2025, has the relationship between shutdown-related emotions and market outcomes weakened, shortened the time lag, or undergone other changes, and does its evolution pattern conform to the expectations that investors draw lessons from previous crises?

1.3 Hypothesis 

Based on the above research questions, this paper proposes the following two hypotheses:

Hypothesis 1: The sentiment related to government shutdowns is positively correlated with the next day’s stock market return and negatively correlated with today’s volatility index. This effect should be particularly significant during the shutdown period.

Hypothesis 2: As investors experience multiple shutdown events, they will regard them as a normalized political event. Thus, the impact of these events on the stock market returns will gradually weaken, which shows a market learning effect. This means that the correlation between sentiment and stock market returns during the 2025 shutdown period will be significantly lower than during the 2018-2019 period.

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