Work detail

Estimation of VaR in Risk Management by Employing Economic News in GARCH Models

Author: Mgr. Ondřej Šindelka
Year: 2012 - summer
Leaders: doc. PhDr. Jozef Baruník Ph.D.
Work type: Finance, Financial Markets and Banking
Language: English
Pages: 138
Awards and prizes: M.A. with distinction from the Dean of the Faculty of Social Sciences for an extraordinarily good masters diploma thesis.
Abstract: We examined the influence of news, related to the main central banks, on the conditional volatility of the
stock returns of eighteen major European banks. We model their conditional volatility with GARCH,
EGARCH and TGARCH models plugging in variables representing news. As a practical application we
evaluate whether applying the news into the volatility modeling improves the performance of the
Value-at-Risk (VaR) measure for given banks. The two types of news variables we use are constructed
from the press releases of main central banks and from the search query at Factiva Dow Jones news
database. The information contained in news is proxied by daily news counts. Using the EGARCH setup
we are able to model individual volatility reaction functions of the banks’ stock returns to different news
variables. We show that the content, origin of the news and also the amount of news (news count) matter
to the conditional volatility behavior. The results confirm that increase in the amount of media coverage
causes increase in volatility. Certain news types have calming effect (speeches of the central banks’
representatives) on volatility while others stir it (monetary news). Finally, we conclude that adding the
news into the modeling only slightly improves the VaR out-of-sample performance.
Downloadable: Master Theses of Sindelka


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