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Extreme losses of portfolios with heavy-tailed components are studied in the framework of multivariate regular variation. Asymptotic distributions of extreme portfolio losses are characterized by a functional γ ξ =γ ξ (α,Ψ) of the tail index α, the spectral measure Ψ, and the vector ξ of portfolio weights. Existence, uniqueness, and location of the optimal portfolio are analysed and applied to the minimization of risk measures. It is shown that diversification effects are positive for α>1 and negative for α<1. Strong consistency and asymptotic normality are established for a semiparametric estimator of the mapping ξ ↦ γ ξ . Strong consistency is also established for the estimated optimal portfolio.
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... Regarding the optimization problem (22) it is convenient to switch to the induced distributions of Y , see also Section 3.1. Thus we assume that Ω = [0, 1] and F is the respective Borel σ-algebra, and that Y (ω) = ω. ...
... In recent years diversification effects in heavy-tailed portfolios received considerable attention; see [21,22,34]. Suppose that Z is a d-dimensional vector of dependent risk factors, and consider the portfolio P = d i=1 w i Z i , where w 1 , . . . ...
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