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Taschenbuch. Condizione: Neu. Copula modeling of tail dependence in the BRIC countries | Implications for value-at-risk and expected shortfall | Mathijs Hitzerd | Taschenbuch | 64 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783848410460 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This paper tests for differences between Value-at-Risk (VaR) and Expected Shortfall (ES) estimates from a euro-investor perspective. Using a copula approach compared to normality assumptions for the BRIC stock markets, using data between January 2007 and December 2010. VaR and ES are estimated using standard normality assumptions and with the use of copulas in which first the markets marginal distributions are estimated, after which the right copula for the indicated dependence between markets is determined based on maximum likelihood and Kendall s tau estimates. Employing Monte Carlo simulation, this research finds that daily VaR estimates can be as much as 1.73% higher for those based on copulas. This effect is mainly caused by the presence of tail dependence in the markets under research. Similarly, ES estimates differ up to 4.19%. This research therefore indicates that risk measures based on normality assumptions severely underestimate risk in these markets due to their inability to take tail dependence into account. 64 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Hitzerd MathijsMathijs Hitzerd studied Business Studies at the University of Amsterdam and graduated cum laude in 2011. During his college years he developed an interest in economics combined with mathematics. The combination is visi.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This paper tests for differences between Value-at-Risk (VaR) and Expected Shortfall (ES) estimates from a euro-investor perspective. Using a copula approach compared to normality assumptions for the BRIC stock markets, using data between January 2007 and December 2010. VaR and ES are estimated using standard normality assumptions and with the use of copulas in which first the markets' marginal distributions are estimated, after which the right copula for the indicated dependence between markets is determined based on maximum likelihood and Kendall's tau estimates. Employing Monte Carlo simulation, this research finds that daily VaR estimates can be as much as 1.73% higher for those based on copulas. This effect is mainly caused by the presence of tail dependence in the markets under research. Similarly, ES estimates differ up to 4.19%. This research therefore indicates that risk measures based on normality assumptions severely underestimate risk in these markets due to their inability to take tail dependence into account.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This paper tests for differences between Value-at-Risk (VaR) and Expected Shortfall (ES) estimates from a euro-investor perspective. Using a copula approach compared to normality assumptions for the BRIC stock markets, using data between January 2007 and December 2010. VaR and ES are estimated using standard normality assumptions and with the use of copulas in which first the markets marginal distributions are estimated, after which the right copula for the indicated dependence between markets is determined based on maximum likelihood and Kendall s tau estimates. Employing Monte Carlo simulation, this research finds that daily VaR estimates can be as much as 1.73% higher for those based on copulas. This effect is mainly caused by the presence of tail dependence in the markets under research. Similarly, ES estimates differ up to 4.19%. This research therefore indicates that risk measures based on normality assumptions severely underestimate risk in these markets due to their inability to take tail dependence into account.