Geodesic
Statistical methods and mathematical models of financial risks estimating
Matematičeskoe modelirovanie, Tome 16 (2004) no. 5, pp. 40-54.

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The methods are considered for estimating and modeling financial risks. The methods for risk measures evaluating under market stress are shown to be most applicable. Extensive computer experiments for different historical financial data have been done to demonstrate their effectivity. 
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E. Yu. Shchetinin; A. S. Lapushkin. Statistical methods and mathematical models of financial risks estimating. Matematičeskoe modelirovanie, Tome 16 (2004) no. 5, pp. 40-54. http://geodesic.mathdoc.fr/item/MM_2004_16_5_a3/

[1] Basel Committee on Banking Supervision, Amendment to the capital accord to incorporate market risks, Basel Commitee Publications, Bank of International Settlements, 1996

[2] R. A. Fisher, L. H. Tippet, “Limiting forms of the frequency distribution of the largest or smallest number of the sample”, Proc. Cambridge Phil. Soc., 24 (1928) | DOI | Zbl

[3] J. Galambos, The asymptotic theory of extreme order statistics, J. Wiley Sons, N.Y., 1978 | MR | Zbl

[4] Gnedenko B. V., “Predelnye teoremy dlya maksimalnogo chlena variatsionnogo ryada”, DAN SSSR, 32:1 (1941), 7–9 | MR | Zbl

[5] Gnedenko B., “Sur la distribution limite du terme maximum dvune serie aleatoire”, Annals of Mathematics, 44 (1944), 423–453 | DOI | MR

[6] Dacorogna M. M., Muller U. A., Pictet O. V. and de Vries C. G., The distribution of extremal Foreign Exchange rate returns in extremely large data sets, Tinbergen Institute, International and Development Economics, TI-95-70

[7] Embrechts P., Kluppelberg C., Mikosch T., Modelling extremal events for insurance and finance, Springer, Berlin, 1997 | MR | Zbl

[8] Lapushkin A. S., Shchetinin Eu. Yu., “Extreme events risk management based on excesses over threshold model”, 5-th International Congress on mathematical modelling, Book of Abstracts, 2, 2002, 165 pp.

[9] Balkema A., de Haan L., “Residual life time at great age”, Annals of Probability, 1974, 792–804 | DOI | MR | Zbl

[10] Pickands J., “Statistical inference using extreme order statistics”, Annals of Statistics, 3 (1975), 119–131 | DOI | MR | Zbl

[11] Hosking J., Wallis J., “Parameter and quantile estimation for the generalized Pareto distribution”, Technometrics, 29 (1989), 339–349 | DOI | MR

[12] http://www.economagic.com

[13] Hill B., “A simple approach to inference about the tail of a distribution”, Annals of Statistics, 3 (1975), 1163–1174 | DOI | MR | Zbl

[14] Haan L. de, Resnik S., “On asymptotic normality of the Hill estimator”, Stoch. Mod., 12 (1996), 699–724 | DOI

[15] Resnick S., “Satrica C Smoothing the Hill estimator”, Journal of Applied Probability, 33 (1996), 139–167 | MR