Original scientific paper
https://doi.org/10.1080/1331677X.2017.1305773
GARCH models in value at risk estimation: empirical evidence from the Montenegrin stock exchange
Julija Cerović Smolović
Milena Lipovina-Božović
Saša Vujošević
Abstract
This article considers the adequacy of generalised autoregressive
conditional heteroskedasticity (GARCH) model use in measuring risk
in the Montenegrin emerging market before and during the global
financial crisis. In particular, the purpose of the article is to investigate
whether GARCH models are accurate in the evaluation of value at risk
(VaR) in emerging stock markets such as the Montenegrin market.
The daily return of the Montenegrin stock market index MONEX is
analysed for the period January 2004–February 2014. The motivation
for this research is the desire to approach quantifying and managing
risk in Montenegro more thoroughly, using methodology that has
not been used for emerging markets so far. Our backtesting results
showed that none of the eight models passed the Kupiec test with
95% of confidence level, while only the ARMA (autoregressive movingaverage
model) (1,2)–N GARCH model did not pass the Kupiec test
with a confidence level of 99%. The results of the Christoffersen test
revealed three models (ARMA(1,2)–TS GARCH(1,1) with a Student-t
distribution of residuals, the ARMA(1,2)–T GARCH(1,1) model with a
Student-t distribution of residuals, and ARMA(1,2)–EGARCH(1,1) with
a reparameterised unbounded Johnson distribution [JSU] distribution
of residuals) which passed the joint Christoffersen test with a 95%
confidence level. It seems that these three models are appropriate for
capturing volatility clustering, since all of them failed for a number of
exceptions. Finally, none of the analysed models passed the Pearson’s
Q test, whether with 90%, 95% or 99%.
Keywords
Value at risk (VaR); fat tails; GARCH models; Kupiec test; Christoffersen test; Pearson’s Q test
Hrčak ID:
180831
URI
Publication date:
1.12.2017.
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