Advanced

The Leverage Effect - Uncovering the true nature of U.S. asymmetric volatility

Dahlvid, Christoffer LU and Granberg, Per (2017) NEKN02 20171
Department of Economics
Abstract
The topic of this thesis is the leverage effect i.e. asymmetric volatility. The leverage effect describes the negative relationship between asset value and volatility. The purpose is to examine if firm specific variables impact the size of the leverage effect, in order to bring additional insights into the missing gap in the research field. The study is conducted on 1,311 U.S. companies active on NASDAQ or the New York Stock Exchange (NYSE) between 1996 and 2015. Two GARCH models are applied to estimate the asymmetric volatility; the GJR-GARCH(1,1) and the EGARCH(1,1) models. Panel data models are used in order to investigate how the firm specific variables influence the leverage effect. The findings of this paper show that two out of the... (More)
The topic of this thesis is the leverage effect i.e. asymmetric volatility. The leverage effect describes the negative relationship between asset value and volatility. The purpose is to examine if firm specific variables impact the size of the leverage effect, in order to bring additional insights into the missing gap in the research field. The study is conducted on 1,311 U.S. companies active on NASDAQ or the New York Stock Exchange (NYSE) between 1996 and 2015. Two GARCH models are applied to estimate the asymmetric volatility; the GJR-GARCH(1,1) and the EGARCH(1,1) models. Panel data models are used in order to investigate how the firm specific variables influence the leverage effect. The findings of this paper show that two out of the eight used variables significantly impact the leverage effect; the firm size and the beta. One of the variables deemed insignificant is the debt-to-equity ratio, which contradicts the original hypothesis behind the leverage effect by Black (1976). Thus, this study concludes that firm specific variables impact the size of the leverage effect. However, the deemed insignificance for six of the variables show that not all variables influence the leverage effect. Furthermore, the sign and the size of the coefficients differ between the variables, with some being more influential than others. (Less)
Please use this url to cite or link to this publication:
author
Dahlvid, Christoffer LU and Granberg, Per
supervisor
organization
course
NEKN02 20171
year
type
H1 - Master's Degree (One Year)
subject
keywords
Leverage effect, asymmetric volatlity, firm specific variables, volatility, GJR-GARCH, EGARCH, panel data
language
English
id
8914682
date added to LUP
2017-06-13 15:19:31
date last changed
2017-06-13 15:19:31
@misc{8914682,
  abstract     = {The topic of this thesis is the leverage effect i.e. asymmetric volatility. The leverage effect describes the negative relationship between asset value and volatility. The purpose is to examine if firm specific variables impact the size of the leverage effect, in order to bring additional insights into the missing gap in the research field. The study is conducted on 1,311 U.S. companies active on NASDAQ or the New York Stock Exchange (NYSE) between 1996 and 2015. Two GARCH models are applied to estimate the asymmetric volatility; the GJR-GARCH(1,1) and the EGARCH(1,1) models. Panel data models are used in order to investigate how the firm specific variables influence the leverage effect. The findings of this paper show that two out of the eight used variables significantly impact the leverage effect; the firm size and the beta. One of the variables deemed insignificant is the debt-to-equity ratio, which contradicts the original hypothesis behind the leverage effect by Black (1976). Thus, this study concludes that firm specific variables impact the size of the leverage effect. However, the deemed insignificance for six of the variables show that not all variables influence the leverage effect. Furthermore, the sign and the size of the coefficients differ between the variables, with some being more influential than others.},
  author       = {Dahlvid, Christoffer and Granberg, Per},
  keyword      = {Leverage effect,asymmetric volatlity,firm specific variables,volatility,GJR-GARCH,EGARCH,panel data},
  language     = {eng},
  note         = {Student Paper},
  title        = {The Leverage Effect - Uncovering the true nature of U.S. asymmetric volatility},
  year         = {2017},
}