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The global digital divide and the changing information flows
Melicharová, Eliška ; Parízek, Michal (advisor) ; Plechanovová, Běla (referee)
The thesis deals with the global information flows and its aim is to find factors which influence them. Firstly, the visibility of the country in international news is explored, i.e. which countries are dominantly represented in the international news. Secondly, the exposure of the country towards international news is observed, i.e how countries vary in the openness towards the international news. The thesis also seek to reveal factors which have an impact on the visibility of the country and on the exposure. The thesis consists of a recherche part with the theory of globalization and a quantitative analysis based on the dataset from 2014-2017. The thesis concludes that countries are represented unevenly with few dominant countries (the most dominant country is China, followed by USA and Ukraine) in the international news and that the most exposed countries have been found small developing countries (Saint Lucia, Antigua and Barbuda, etc.) from South America. Regarding the factors of visibility of the country, the highest impact has the size of population,and also GNI and the presence of violent correlated. On the contrary, all factors impacting the exposure of the country were found statistically insignificant.
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Estimation of VaR in Risk Management by Employing Economic News in GARCH Models
Šindelka, Ondřej ; Baruník, Jozef (advisor) ; Jakubík, Petr (referee)
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.
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