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Publications in Math-Net.Ru
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Hedging problem for the Asian call options with transaction costs
Teor. Veroyatnost. i Primenen., 68:2 (2023), 253–276
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Super-efficient robust estimation in Lévy continuous time regression models from discrete data
Vestn. Tomsk. Gos. Univ. Mat. Mekh., 2023, no. 85, 22–31
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Approximate hedging with constant proportional transaction costs in financial markets with jumps
Teor. Veroyatnost. i Primenen., 65:2 (2020), 281–311
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Improved model selection method for an adaptive estimation in semimartingale regression models
Vestn. Tomsk. Gos. Univ. Mat. Mekh., 2019, no. 58, 14–31
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Sequential $\delta$-optimal consumption and investment for stochastic volatility markets with unknown parameters
Teor. Veroyatnost. i Primenen., 60:4 (2015), 628–659
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Estimation of the regression with a pulse noise by discrete time observations
Teor. Veroyatnost. i Primenen., 58:3 (2013), 454–471
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Nonparametric estimation in a semimartingale regression model. Part 2. Robust asymptotic efficiency
Vestn. Tomsk. Gos. Univ. Mat. Mekh., 2009, no. 4(8), 31–45
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Non-parametric estimation in a semimartingale regression model. Part 1. Oracle inequalities
Vestn. Tomsk. Gos. Univ. Mat. Mekh., 2009, no. 3(7), 23–41
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Nonparametric Estimation for an Autoregressive Model
Vestn. Tomsk. Gos. Univ. Mat. Mekh., 2008, no. 2(3), 20–30
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On the Guaranteed Parameter Estimation in Linear Regression Subject to Dependent Noise
Avtomat. i Telemekh., 1997, no. 2, 75–87
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Guaranteed Estimation of a Periodic Signal Distorted by an Autoregressive Noise with Unknown Parameters
Probl. Peredachi Inf., 33:4 (1997), 26–44
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The prescribed precision estimators of the autoregression parameter using the generalized least square method
Teor. Veroyatnost. i Primenen., 41:4 (1996), 765–784
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On the estimation of an autoregressive parameter on the basis of the generalized method of least squares
Uspekhi Mat. Nauk, 50:6(306) (1995), 187–188
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Large deviations for solutions of singularly perturbed stochastic differential equations
Uspekhi Mat. Nauk, 50:5(305) (1995), 147–172
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Asymptotic expansions for a model with distinguished “fast” and “slow” variables, described by a system of singularly perturbed stochastic differential equations
Uspekhi Mat. Nauk, 49:4(298) (1994), 3–46
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Guaranteed estimation of autoregression parameters on the basis of a sequential correlational method
Trudy Mat. Inst. Steklov., 202 (1993), 149–169
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Sequential Parameter Estimation with Guaranteed Mean-Square Accuracy for Unstable Linear Stochastic Systems
Probl. Peredachi Inf., 28:4 (1992), 35–48
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Sequential Estimation of the Parameter of a Stochastic Difference Equation with Random Coefficients
Teor. Veroyatnost. i Primenen., 37:3 (1992), 482–501
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Sets of accesibility for controlled stochastic differential equations
Uspekhi Mat. Nauk, 46:1(277) (1991), 209–210
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Asymptotic properties of a sequential plan for estimating a first-order autoregression parameter
Teor. Veroyatnost. i Primenen., 36:1 (1991), 42–53
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Singularly perturbed stochastic equations and partial differential
equations
Dokl. Akad. Nauk SSSR, 311:5 (1990), 1039–1042
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Singular perturbations of stochastic differential equations
Mat. Sb., 181:9 (1990), 1170–1182
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On guaranteed parameter estimation for unstable dynamic systems
Avtomat. i Telemekh., 1988, no. 11, 130–141
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On Sequential Estimation of Parameters of Diffusion Processes
Probl. Peredachi Inf., 21:1 (1985), 48–61
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Asymptotic normality of sequential parameter estimation for dynamic systems
Avtomat. i Telemekh., 1984, no. 12, 56–63
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Successive procedures of parameter identification in dynamic systems
Avtomat. i Telemekh., 1981, no. 7, 84–92
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In memory of Prof. G. G. Pestov: life and scientific-educational activity
Vestn. Tomsk. Gos. Univ. Mat. Mekh., 2015, no. 5(37), 103–114
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