Giovanni Masala
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6 publications
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545 downloads
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1788 views
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Optimisation of Conditional-VaR in an Actuarial Model for Credit Risk Assuming a Student Copula Dependence Structure
Investment Management and Financial Innovations Volume 4, 2007 Issue #3
Views: 580 Downloads: 173 TO CITE -
Advanced operational risk modelling in banks and insurance companies
Investment Management and Financial Innovations Volume 6, 2009 Issue #3
Views: 620 Downloads: 267 TO CITE -
Loss-Alae modeling through a copula dependence structure
Investment Management and Financial Innovations Volume 6, 2009 Issue #4
Views: 539 Downloads: 258 TO CITE -
Electricity load modeling: an application to Italian market
Investment Management and Financial Innovations Volume 12, 2015 Issue #1 pp. 35-46
Views: 544 Downloads: 259 TO CITE -
Dynamic dependence structure between energy markets and the Italian stock index
Investment Management and Financial Innovations Volume 15, 2018 Issue #2 pp. 60-67
Views: 1189 Downloads: 146 TO CITE АНОТАЦІЯThe dependence structure between the main energy markets (such as crude oil, natural gas, and coal) and the main stock index plays a crucial role in the economy of a given country. As the dependence structure between these series is dramatically complex and it appears to change over time, time-varying dependence structure given by a class of dynamic copulas is taken into account.
To this end, each pair of time series returns with a dynamic t-Student copula is modelled, which takes as input the time-varying correlation. The correlation evolves with the DCC(1,1) equation developed by Engle.
The model is tested through a simulation by employing empirical data issued from the Italian Stock Market and the main connected energy markets. The author considers empirical distributions for each marginal series returns in order to focus on the dependence structure. The model’s parameters are estimated by maximization of the log-likelihood. Also evidence is found that the proposed model fits correctly, for each pair of series, the left tail dependence coefficient and it is then compared with a static copula dependence structure which clearly underperforms the number of joint extreme values at a given confidence level.
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