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 non-parametric 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 back-testing 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 Peak-Over Threshold approaches with Mixing Unconditional Disturbances. This method can be an effective tool to create value for stress-testing valuation.
Item Type: | MPRA Paper |
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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, Peak-Over 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.uni-muenchen.de/id/eprint/17482 |