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.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:307458 |
| Date | January 2012 |
| Creators | Šindelka, Ondřej |
| Contributors | Baruník, Jozef, Jakubík, Petr |
| Source Sets | Czech ETDs |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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