Investigating the Relationship Between Central Bank Transparency and Stock Market Volatility in a Nonparametric Framework
Year: 2017
Author: Papadamou, Stephanos, Sidiropoulos, Moïse, Tzeremes, Nickolaos
Credit and Capital Markets – Kredit und Kapital, Vol. 50 (2017), Iss. 1 : pp. 63–83
Abstract
This study investigates whether any non-linear relationship exists between central bank transparency and stock market variability in a non-parametric framework for a large number of countries. Our findings imply that a high level of transparency can significantly reduce historical as well as conditional stock market volatility in a non-linear manner. The negative effect of transparency on stock volatility is clearer when we move from low levels towards higher levels of transparency; this effect diminishes as long as we move to higher levels of transparency. This analysis implies that monetary authorities can contribute to equity market stability by adopting more transparent monetary policies in the early stages.
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.3790/ccm.50.1.63
Credit and Capital Markets – Kredit und Kapital, Vol. 50 (2017), Iss. 1 : pp. 63–83
Published online: 2017-03
AMS Subject Headings: Duncker & Humblot
Copyright: COPYRIGHT: © Global Science Press
Pages: 21
Keywords: E52 E5 C14 Local linear estimators nonparametric regression central bank transparency