| dc.description.abstract | Value-at-risk (VaR) is known as the popular measurement for risk of loss in nance.
Meanwhile, there are a lot of ways that can use to estimate VaR, such as historical
simulation, the variance-covariance, and the Monte Carlo approaches. This research
will represent copula as one of the useful ways to estimate VaR which help us in
modeling multivariate distributions. It follows the de nition of the joint distribution,
marginal distribution and the dependence between random variables. We also present
an application to nancial stock markets. Then, the estimated copula will give the
joint probabilities of losses and also let us know more about their level curves which
measure the trade-o that can be exploited for economic capital allocation.
Key words: VaR, copula, level curves, capital allocation. | en_US |
