Estimating downside risk in stock returns under structural breaks

We show with simulations that inducing structural breaks in the volatility of returns causes non-normality by significantly increasing kurtosis. We endogenously detect significant structural breaks in the volatility of US stock returns and incorporate this information to estimate Value-at-Risk (VaR)...

Full description

Saved in:
Bibliographic Details
Published inInternational review of economics & finance Vol. 58; pp. 102 - 112
Main Authors Hood, Matthew, Malik, Farooq
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.11.2018
Subjects
GARCH
Structural breaks
Volatility
Structural breaks
GARCH
G1
Volatility
Online AccessGet full text

Cover

More Information
Summary:We show with simulations that inducing structural breaks in the volatility of returns causes non-normality by significantly increasing kurtosis. We endogenously detect significant structural breaks in the volatility of US stock returns and incorporate this information to estimate Value-at-Risk (VaR) to measure the downside risk. Out-of-sample performance results indicate that our proposed model, which incorporates both time varying volatility and structural breaks in volatility, produces more accurate VaR forecasts than several benchmark methods. We highlight the economic importance of our results by calculating the daily capital charges using the Basel Accords. •Simulations show that inducing structural breaks in returns increases kurtosis.•Value-at-Risk forecasts are improved when structural breaks are incorporated.•Economic importance of results is highlighted by calculating capital charges.
ISSN:1059-0560
1873-8036
DOI:10.1016/j.iref.2018.03.002