I quantify the relationship between political uncertainty and equity volatility in the months around US elections from 1989-2012. The Economic Policy Uncertainty Index and Stockholm International Peace Research Institute (SIPRI) data are employed to measure political uncertainty faced by military contractors, capitalizing on the unique monopsony-oligopoly business environment of these firms. I employ a GARCH (1,1) model with cross-sectionally correlated moments to produce daily firm-election volatility measures. Volatility increases 11% for local, 27% for midterm, and 43% for presidential elections. These measures demonstrate that all election categories: local, federal, presidential, and midterm exhibit differential effects on equity volatility. My results contrast prior equity volatility research, showing that equity volatility increases much earlier but more gradually for US elections than for international (parliamentary) elections. I show that the political uncertainty index values in September predict the equity volatility before, during, and after November elections. I present a parsimonious piecewise function to model the distinct and predictable daily equity volatility profile in the months around US elections.
","abstract_html":"<p>I quantify the relationship between political uncertainty and equity volatility in the months around US elections from 1989-2012. The Economic Policy Uncertainty Index and Stockholm International Peace Research Institute (SIPRI) data are employed to measure political uncertainty faced by military contractors, capitalizing on the unique monopsony-oligopoly business environment of these firms. I employ a GARCH (1,1) model with cross-sectionally correlated moments to produce daily firm-election volatility measures. Volatility increases 11% for local, 27% for midterm, and 43% for presidential elections. These measures demonstrate that all election categories: local, federal, presidential, and midterm exhibit differential effects on equity volatility. My results contrast prior equity volatility research, showing that equity volatility increases much earlier but more gradually for US elections than for international (parliamentary) elections. I show that the political uncertainty index values in September predict the equity volatility before, during, and after November elections. I present a parsimonious piecewise function to model the distinct and predictable daily equity volatility profile in the months around US elections.</p>","abstract_has_math":false,"creators":["Ross, Matthew Mark"],"institution":null,"degree_name":"Ph.D.","degree_level":"Open Access Dissertation","degree_discipline":"Management and Information Systems","degree_department":null,"school":null,"contributors":["Mbodja Mougoué"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-01-01T08:00:00Z","date_published":"2014-01-01T08:00:00Z","updated_at":"2026-07-24T05:59:39Z","subjects":["Asset Pricing","Equity Volatility","Military Contractors","Political Uncertainty","Finance and Financial Management","Other Economics","Political Science"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.wayne.edu/oa_dissertations/996","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Mbodja Mougoué"]},{"key":"dc:creator","label":"Author","values":["Ross, Matthew Mark"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2014-01-01T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Management and Information Systems"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Asset Pricing","Equity Volatility","Military Contractors","Political Uncertainty","Finance and Financial Management","Other Economics","Political Science"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.wayne.edu/oa_dissertations/996"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["I quantify the relationship between political uncertainty and equity volatility in the months around US elections from 1989-2012. The Economic Policy Uncertainty Index and Stockholm International Peace Research Institute (SIPRI) data are employed to measure political uncertainty faced by military contractors, capitalizing on the unique monopsony-oligopoly business environment of these firms. I employ a GARCH (1,1) model with cross-sectionally correlated moments to produce daily firm-election volatility measures. Volatility increases 11% for local, 27% for midterm, and 43% for presidential elections. These measures demonstrate that all election categories: local, federal, presidential, and midterm exhibit differential effects on equity volatility. My results contrast prior equity volatility research, showing that equity volatility increases much earlier but more gradually for US elections than for international (parliamentary) elections. I show that the political uncertainty index values in September predict the equity volatility before, during, and after November elections. I present a parsimonious piecewise function to model the distinct and predictable daily equity volatility profile in the months around US elections.
"]},{"key":"dc:title","label":"Title","values":["Elections And Asset Pricing: The Politically Sensitive Equity Of Us Military Contractors"]}]}],"canonical_facts":{"dc:contributor":["Mbodja Mougoué"],"dc:creator":["Ross, Matthew Mark"],"dc:date.available":["2014-01-01T08:00:00Z"],"dc:description.abstract":["I quantify the relationship between political uncertainty and equity volatility in the months around US elections from 1989-2012. The Economic Policy Uncertainty Index and Stockholm International Peace Research Institute (SIPRI) data are employed to measure political uncertainty faced by military contractors, capitalizing on the unique monopsony-oligopoly business environment of these firms. I employ a GARCH (1,1) model with cross-sectionally correlated moments to produce daily firm-election volatility measures. Volatility increases 11% for local, 27% for midterm, and 43% for presidential elections. These measures demonstrate that all election categories: local, federal, presidential, and midterm exhibit differential effects on equity volatility. My results contrast prior equity volatility research, showing that equity volatility increases much earlier but more gradually for US elections than for international (parliamentary) elections. I show that the political uncertainty index values in September predict the equity volatility before, during, and after November elections. I present a parsimonious piecewise function to model the distinct and predictable daily equity volatility profile in the months around US elections.
"],"dc:identifier":["https://digitalcommons.wayne.edu/oa_dissertations/996"],"dc:subject":["Asset Pricing","Equity Volatility","Military Contractors","Political Uncertainty","Finance and Financial Management","Other Economics","Political Science"],"dc:title":["Elections And Asset Pricing: The Politically Sensitive Equity Of Us Military Contractors"],"thesis:degree_discipline":["Management and Information Systems"],"thesis:degree_level":["Open Access Dissertation"],"thesis:degree_name":["Ph.D."]},"updated_at":"2026-07-24T05:59:39Z"}