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Value-at-Risk (VaR) is one of risk measuring tools widely used at this time. There are several approaches for calculating VaR, such as historical simulation, the variance-covariance, and Monte Carlo simulation. If a portfolio has two kind of variables in there, then we need consider dependence betwe...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/18774 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Value-at-Risk (VaR) is one of risk measuring tools widely used at this time. There are several approaches for calculating VaR, such as historical simulation, the variance-covariance, and Monte Carlo simulation. If a portfolio has two kind of variables in there, then we need consider dependence between them. The copula theory s a fundamental tool in modelling bivariate distributions. It come within joint distribution of each marginal distributions and the dependence between them, so copula is the right tool to modelling variables which have dependence. One of extend theory of copula is conditional copula, whose components are conditional marginal distributions. It has dynamic structure, so it could used for data whose time variation. This research used conditional copula to calculate VaR of a portfolio composed by Nasdaq and S&P 500 stock indices. |
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