  In this paper, we investigate risk measures such as value at risk (VaR) and
the conditional tail expectation (CTE) of the extreme (maximum and minimum) and
the aggregate (total) of two dependent risks. In finance, insurance and the
other fields, when people invest their money in two or more dependent or
independent markets, it is very important to know the extreme and total risk
before the investment. To find these risk measures for dependent cases is quite
challenging, which has not been reported in the literature to the best of our
knowledge. We use the FGM copula for modelling the dependence as it is
relatively simple for computational purposes and has empirical successes. The
marginal of the risks are considered as exponential and pareto, separately, for
the case of extreme risk and as exponential for the case of the total risk. The
effect of the degree of dependency on the VaR and CTE of the extreme and total
risks is analyzed. We also make comparisons for the dependent and independent
risks. Moreover, we propose a new risk measure called median of tail (MoT) and
investigate MoT for the extreme and aggregate dependent risks.
