Mutual Fund Volatility in Election Years: Low Risk or High Risk?

This research aims to analyze the patterns of price fluctuations in mutual funds over a specific time frame, particularly in relation to political events such as national elections. The primary objective is to evaluate the risk levels of mutual funds in countries undergoing election cycles, which are often associated with heightened economic and political uncertainty. To achieve this, the study employs Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized ARCH (GARCH) models—two widely recognized econometric tools for analyzing time series data exhibiting volatility clustering. These models enable the classification and comparison of both low and high volatility conditions in mutual fund performance. The dataset comprises mutual fund data from 10 different countries, covering the period between 2019 and 2024. Each selected country has a mature mutual fund market with a focus on equity (stocks) and fixed-income (bonds) instruments. The findings reveal distinct variations in volatility levels among the countries studied, influenced by their respective political climates during election periods. The application of ARCH and GARCH modeling proves effective in capturing these fluctuations. The results offer valuable insights for investors seeking to minimize risk by diversifying their portfolios across more stable mutual funds, especially during times of political transition. This research contributes to better-informed investment decision-making in politically dynamic environments.