Comparison of Certain Models and Results of Stochastic Financial Mathematics with Real Data
Informatics and Automation, Stochastic financial mathematics, Tome 237 (2002), pp. 302-319.

Voir la notice de l'article provenant de la source Math-Net.Ru

Certain probabilistic models for the logarithmic increments of stock prices are compared with real data. It is shown that all these models are essentially inadequate because of the statistical instability of the observed data. Nevertheless, theoretical results on option hedging are confirmed (to unexpectedly high accuracy) by hedging simulations using real price data. This fact is explained by comparatively small fluctuations of the volatility of prices, which are the main source of imbalance (i.e. the hedging inaccuracy).
@article{TRSPY_2002_237_a19,
     author = {V. N. Tutubalin},
     title = {Comparison of {Certain} {Models} and {Results} of {Stochastic} {Financial} {Mathematics} with {Real} {Data}},
     journal = {Informatics and Automation},
     pages = {302--319},
     publisher = {mathdoc},
     volume = {237},
     year = {2002},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/TRSPY_2002_237_a19/}
}
TY  - JOUR
AU  - V. N. Tutubalin
TI  - Comparison of Certain Models and Results of Stochastic Financial Mathematics with Real Data
JO  - Informatics and Automation
PY  - 2002
SP  - 302
EP  - 319
VL  - 237
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/TRSPY_2002_237_a19/
LA  - ru
ID  - TRSPY_2002_237_a19
ER  - 
%0 Journal Article
%A V. N. Tutubalin
%T Comparison of Certain Models and Results of Stochastic Financial Mathematics with Real Data
%J Informatics and Automation
%D 2002
%P 302-319
%V 237
%I mathdoc
%U http://geodesic.mathdoc.fr/item/TRSPY_2002_237_a19/
%G ru
%F TRSPY_2002_237_a19
V. N. Tutubalin. Comparison of Certain Models and Results of Stochastic Financial Mathematics with Real Data. Informatics and Automation, Stochastic financial mathematics, Tome 237 (2002), pp. 302-319. http://geodesic.mathdoc.fr/item/TRSPY_2002_237_a19/

[1] Mandelbrot B. B., Fractals and scaling in finance. Discontinuity, concentration, risk, Springer-Verl., New York etc., 1997, 551 pp. | MR | Zbl

[2] Eberlein E., Keller U., Prause K., “New insights into smile, mispricing, and value at risk: the hyperbolic model”, J. Business, 71:3 (1998), 371–405 | DOI | MR

[3] Eberlein E., Recent advances in more realistic market and credit risk management: the hyperbolic model, Preprint Inst. Math. Stochastic Univ., Freiburg, 2000, Febr. 25

[4] Selezneva T. V., Tutubalin V. N., Uger E. G., “Issledovanie prikladnykh vozmozhnostei nekotorykh modelei stokhasticheskoi finansovoi matematiki”, Obozr. prikl. i promyshl. matematiki, 7:2 (2000), 210–238

[5] Shiryaev A. N., Osnovy stokhasticheskoi finansovoi matematiki. T. 1: Fakty. Modeli, Fazis, M., 1998; Т. 2: Теория

[6] Stepanov N. M., Volatilnosti i disbalansy pri khedzhirovanii optsionov, Dipl. rabota, Mekh.-mat. fak. MGU, M., 2000

[7] Lamburt V. G., “Sravnenie nekotorykh strategii khedzhirovaniya platezhnykh obyazatelstv, ispolzuyuschikh i ne ispolzuyuschikh martingalnuyu meru”, Obozr. prikl. i promyshl. matematiki, 8:1 (2001) | Zbl