Does partisan conflict predict a reduction in US stock market (realized) volatility? Evidence from a quantile-on-quantile regression model
Loading...
Date
Authors
Gupta, Rangan
Pierdzioch, Christian
Selmi, Refk
Wohar, Mark E.
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
Theory suggests that partisan conflict negatively affects the possibility of economic policy change, implying that financial markets tend to operate under lower policy risk. Given that stock-return volatility measures risk, if the gridlock argument holds, stock–market volatility should be lower under divided than under a unified government. Using a partisan conflict index (PCI), we empirically confirm this theoretical argument for the U.S. stock market based on quantiles-based regressions. In particular, quantile-on-quantile regressions show that PCI tends to predict reduced volatility, with the effect being stronger at levels of volatility that are moderately low (i.e., below the median, but not at its extreme) for an increase in the predictor, especially with moderately low and high initial values (i.e., when PCI is at quantiles around the median).
Description
Keywords
Partisan conflict, Realized volatility, Quantile regressions
Sustainable Development Goals
Citation
Gupta, R., Pierdzioch, C., Selmi, R. & Wohar, M.E. 2018, 'Does partisan conflict predict a reduction in US stock market (realized) volatility? Evidence from a quantile-on-quantile regression model', North American Journal of Economics and Finance, vol. 43, pp. 87-96.