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Aplicacao de Acoplamento no Calculo do Valor em Risco
Company: Universidade Estadual de Campinas
Year Of Publication: 2004
Month Of Publication: March
Pages: 142
Download Count: 256
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Comment Num: 0
Language: EN
Who Can Read: Free
Date: 7-26-2007
Publisher: Administrator
Value at Risk (VaR) has a central role in the risk management. There areseveral approaches for the estimation of VaR, such as the variance-covariance(also known as analytical), the historical simulation and the Monte Carlo approaches.Whereas the first approach does not assume any distribution, thelast two approaches demand the joint distribution to be known, which in theanalytical approach is frequently the normal distribution. The copula theoryis a fundamental tool in the modelling of the (joint) multivariate distribution.It allows the definition of the joint distribution through the marginal distributionsand the dependence between the variables. Recently the copula theoryhas been extended to the conditional case, allowing us the use of copulas tomodel time-varying dependence, which is time varying. Variation in time ofthe first and second conditional moments is widely discussed in the literature,and it is natural to allow for the time variation of the conditional dependenceseems to be natural. This work presents some concepts of copula functions,and some issues involved in the application of the copulas theory in the estimationof VaR of portfolios. The methodology is applied to two portfolios,the first composed by the Sterling Pound/US dollar and the Japanese Yen/USdollar exchange rates, and the second composed by the Nasdaq and S&P500US stock indexes.
Palaro, Helder P. Sign in to follow this author
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