Does partisan conflict predict a reduction in US stock market (realized) volatility? Evidence from a quantile-on-quantile regression model

Loading...
Thumbnail Image

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.