Political Geography and Stock Market Volatility: The Role of Political Alignment across Sentiment Regimes

This paper extends the literature on the nexus between political geography and financial markets to the stock market volatility context by examining the interrelation between political geography and the predictive relation between the state- and aggregate-level stock market volatility via recently constructed measures of political alignment. Using monthly data for the period from February 1994 to March 2023 and a machine learning technique called random forests, we show that the importance of the state-level realized stock market volatilities as a driver of aggregate stock market volatility displays considerable cross- sectional dispersion as well as substantial variation over time, with the state of New York playing a prominent role. Further analysis shows that stronger political alignment of a state with the ruling party is associated with a lower contribution of the state's realized volatility to aggregate stock market volatility, highlighting the role of risk effects associated with the political geography of firms. Finally, we show that the negative link between the political alignment of a state and the importance of that state's realized volatility over aggregate stock market volatility is statistically significant during high-sentiment periods, but weak and statistically insignificant during low-sentiment periods, underscoring the role of investor sentiment for the nexus between political geography and financial markets. Our findings presents new insight to the risk-based arguments that associate political geography with stock market dynamics.