We estimate Value-at-Risk for sums of dependent random variables. We model multivariate dependent random variables using archimedean copulas. This structure allows one to calculate the asymptotic behaviour of extremal events. An important application of such results are Value-at-Risk estimates for sums of dependent random variables.

its most compelling aspect is its vertical variation, that is, the sum of the vertical distances between its adjacent terms. Denoted by varw, the vertical variation of the sequence in (1.1) is varw = 2 + 1 + 0 + 2 + 1 = 6. Our purpose here is to compute the mean and variance of var on four classical sets of combinatorial sequences. To formalize matters and place our problem in the context of ot...

Jamshidian and Zhu (1997) propose a discrete grid method for simplifying the computation of Value at Risk (VaR) for fixed-income portfolios. Their method relies on two simplifications. First, the value of fixed income instruments is modeled as depending on a small number of risk factors chosen using principal components analysis. Second, they use a discrete approximation to the distribution of ...

The aim of this paper is to discuss the use of the Generalized Hyperbolic Distributions to fit Brazilian assets returns. Selected subclasses are compared regarding goodness of fit statistics and distances. Empirical results show that these distributions fit data well. Then we show how to use these distributions in value at risk estimation and derivative price computation.

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This article is devoted to the study cashflow maps used in the computation of value-at-risk (VaR). Properties and characteristics of the approaches found in the literature are presented and two new approaches are introduced. The goal of this paper is to study the quality of these maps. This is done by calculating the risk induced by the difference between the mapped cashflows and the original one.

An approach to VaR (value-at-risk) for capital markets is proposed with Gaussian mixture. Considering the impacts of the components in a Gaussian mixture, an approach to VaR for capital markets is proposed to describe risk structure in capital markets. This approach can be programmed in parallel. Empirical computation of VaR for China securities markets and the Forex markets are provided to dem...