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Convolutions of Heavy Tailed Random Variables and Applications to Portfolio Diversification and MA(1) Time Series

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Author Info
Jaap Geluk () (Econometric Institute, Erasmus University Rotterdam)
Liang Peng (Center for Mathematics and its Applications, Australian National University, Canberra)
Casper G. de Vries () (Erasmus University Rotterdam)

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Abstract

The paper characterizes first and second order tail behavior of convolutions of i.i.d. heavy tailed random variables with support on the real line. The result is applied to the problem of risk diversification in portfolio analysis and to the estimation of the parameter in a MA(1) model.

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Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 99-088/2.

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Date of creation: 18 Nov 1999
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Handle: RePEc:dgr:uvatin:19990088

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Web page: http://www.tinbergen.nl/

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  1. Somnath Datta & William McCormick, 1998. "Inference for the Tail Parameters of a Linear Process with Heavy Tail Innovations," Annals of the Institute of Statistical Mathematics, Springer, vol. 50(2), pages 337-359, June. [Downloadable!] (restricted)
  2. de Haan, L. & Pereira, T. Themido, 1999. "Estimating the index of a stable distribution," Statistics & Probability Letters, Elsevier, vol. 41(1), pages 39-55, January. [Downloadable!] (restricted)
  3. Lii, Keh-Shin & Rosenblatt, Murray, 1992. "An approximate maximum likelihood estimation for non-Gaussian non-minimum phase moving average processes," Journal of Multivariate Analysis, Elsevier, vol. 43(2), pages 272-299, November. [Downloadable!] (restricted)
  4. Jón Daníelsson & Casper G. de Vries, 1998. "Value-at-Risk and Extreme Returns," Tinbergen Institute Discussion Papers 98-017/2, Tinbergen Institute. [Downloadable!]
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  5. Vries, Caspar de & Danielsson, Jon, 1996. "Tail Index and Quantile Estimation with Very High Frequency Data," CESifo Working Paper Series CESifo Working Paper No. , CESifo GmbH.
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