Suarez, Ronny (2009): Improving Modeling of Extreme Events using Generalized Extreme Value Distribution or Generalized Pareto Distribution with Mixing Unconditional Disturbances.

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Abstract
In this paper an alternative nonparametric historical simulation approach, the Mixing Unconditional Disturbances model with constant volatility, where price paths are generated by reshuffling disturbances for S&P 500 Index returns over the period 1950  1998, is used to estimate a Generalized Extreme Value Distribution and a Generalized Pareto Distribution. An ordinary backtesting for period 1999  2008 was made to verify this technique, providing higher accuracy returns level under upper bound of the confidence interval for the Block Maxima and the PeakOver Threshold approaches with Mixing Unconditional Disturbances. This method can be an effective tool to create value for stresstesting valuation.
Item Type:  MPRA Paper 

Original Title:  Improving Modeling of Extreme Events using Generalized Extreme Value Distribution or Generalized Pareto Distribution with Mixing Unconditional Disturbances 
Language:  English 
Keywords:  Extreme Values, Block Maxima, PeakOver Threshold, Mixing Unconditional Disturbances 
Subjects:  C  Mathematical and Quantitative Methods > C0  General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General 
Item ID:  17482 
Depositing User:  Ronny Suarez 
Date Deposited:  23 Sep 2009 19:38 
Last Modified:  01 Oct 2019 17:49 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/17482 