Historical share's behavior accounting
Matematičeskoe modelirovanie, Tome 15 (2003) no. 12, pp. 75-80.

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The models where stock is a lognormal distributed random process are the routine ones. But these models ignore a possible sensitivities of a share's price to the last quotations. In present paper a mathematical model of such kind “memory” accounting is proposed. The model is in concordance with basis postulates of financial mathematics. A contribution of historical stock's behavior is taking into account as additive component in stochastic differential. The effect of the “memory” presence is characterized by time interval $\tau$ that defines the size of the “memory” in the past. A size of the contribution from moment passed is described by weight function.
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D. N. Zhabin. Historical share's behavior accounting. Matematičeskoe modelirovanie, Tome 15 (2003) no. 12, pp. 75-80. http://geodesic.mathdoc.fr/item/MM_2003_15_12_a4/

[1] Wilmott P., Dewynne J., Howison S., Option Pricing: Mathematical Models and Computation, Oxford Financial Press, 1993

[2] Neftci S., An Introduction to the Mathematics of Financial Derivatives, Academic Press, 1996 | Zbl

[3] Hull J., Option Futures and other Derivative Securities, Prentice-Hall, NJ, 1999

[4] Melnikov A. V., Volkov S. N., Nechaev M. L., Matematika finansovykh obyazatelstv, GU VShE, M., 2001

[5] Petere E., Khaos i poryadok na rynke kapitala, M., 2000

[6] Peters E., Fractal Market Analysis. Applying Chaos Theory to Investment and Economics, John Wiley and Sons, Inc., 1994

[7] Gikhman I. I., Skorokhod A. V., Vvedenie v teoriyu sluchainykh protsessov, Nauka, M., 1977 | MR

[8] Bollerslev T., Engle R. F., Nelson D. B., ARCH Models, University of California, San Diego, 1993 | MR

[9] Bollerslev T., “Generalized Autoregressive Conditional Heteroskedasticity”, Journal of Econometrics, 31 (1986), 307–327 | DOI | MR | Zbl

[10] Lucas J. M., Sacucci M. S., “Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements”, Technometric, 31 (1990), 1–29 | DOI | MR

[11] Naukonen M. S., “On the Predictive Ability of Several Common Models of Volatility: An Empirical Test on the FOX Index”, Applied Financial Economics, 12:11 (2002), 813–826 | DOI