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On using bootstrap methods for understanding empirical loss data and dynamic financial analysis

Domenii publicaţii > Ştiinţe informatice + Tipuri publicaţii > Articol în volumul unei conferinţe

Autori: G. Albeanu, H. Madsen, Manuela Ghica, P. Thyregod, F. Popentiu-Vladicescu

Editorial: Peter Goos, ENBIS, ENBIS 7 Dortmund (September 24-26, 2007), CDROM, 2007.


Computer-Intensive methods for estimation assessment provide valuable information concerning the adequacy of applied probabilistic models.

The bootstrap method is an extensive computational approach for understanding empirical data and is based on resampling and statistical estimation. It is a powerful tool, especially when only a small data set is used to predict the behaviour of systems or processes.

This paper describes some case studies based on the Efron type bootstrap approaches [1] for modelling loss distributions [2] and for general dynamic financial analysis [3]. The case studies are inspired from risk management field. The research is based on theoretical previous developments in accuracy assessment [4], reliability estimation [5] and risk exchange modelling [6].

[1] Efron B., Computer-Intensive Methods in Statistical Regression, Siam Review, 30, 3, 421-449, (1988).
[2] Hogg, R.V. and Klugmsn S.A,: Loss distributions, John Wiley & Sons, New York, 1984.
[3] Kaufmann R., Gadmer A. and Kett R.: Introduction to dynamic functional analysis, ETH Zurich, IFOR, 1999, .
[4] Albeanu G.: Resampling Simultaneous Confidence Bands for Nonlinear Explicit Regression Models, Mathematical Reports, 50(5-6), 289-295, (1998).
[5] Albeanu G. and Popentiu F.: On the Bootstrap Method: Software Reliability Assessment and Simultaneous Confidence Bands, Annals of Oradea University, Energetics Series, 7(1), 109-113, (2001).
[6] Manuela Ghica.: A risk exchange model with a mixture exponential utility function, Annals of Bucharest University, Mathematics and Informatics Series, 2006.

Cuvinte cheie: bootstrap, loss distributions, dynamic financial analysis, buisness statistics // bootstrap, loss distributions, dynamic financial analysis, buisness statistics