Copulas as a measure of dependence in skewed portfolios of risk simulation study on financial losses

Abstract EN

In this paper we have implemented copula functions in risk management applications, where randomness plays a big role in portfolios.

We have used its powerful property in sensing the dependency structure of the distribution tail to measure the risk probability that a portfolio of random risk structure may encounter over specified time horizon ahead.

We have used the Monte Carlo simulation to generate the required data to be used in practiced side.

We have performed a practical application with a portfolio of ten Italian equities Copula function represents the dependence structure of a random variable vector.

We concluded that the use of a Clayton copula is better than in the comparison- based on (Vary), used program (R).