Modern stochastics and applications / edited by Volodymyr Korolyuk, Nikolaos Limnios, Yuliya Mishura, Lyudmyla Sakhno, Georgiy Shevchenko.

Springer eBooks

Part I: Probability Distributions in Applications.-Comparing Brownian stochastic integrals for the convex order (Yor, Hirsch) -- Application of ?-sub-Gaussian random processes in queueing theory (Kozachenko, Yamnenko) -- A review on time-changed pseudo processes and the related distributions (Orsingher) -- Reciprocal processes: a stochastic analysis approach (Roelly). Part II: Stochastic Equations -- Probabilistic counterparts of nonlinear parabolic PDE systems (Belopolskaya) -- Finite-time blowup and existence of global positive solutions of semilinear SPDE’s with fractional noise (Dozzi, Kolkovska, López-Mimbela) -- Hydrodynamics and SDE with Sobolev coefficients (Fang) -- Elementary pathwise methods for non-linear parabolic and transport type SPDE with fractal noise (Hinz, Issoglio, Zähle) -- SPDE’s driven by general stochastic measures (Radchenko). Part III: Limit Theorems -- Exponential convergence of multi-dimensional stochastic mechanical systems with switching (Anulova, Veretennikov) -- Asymptotic behaviour of the distribution density of the fractional Lévy motion (Kulik, Knopova).-Large deviations for random evolutions in the scheme of asymptotically small diffusion (Koroliuk, Samoilenko) -- Limit theorems for excursion sets of stationary random fields (Spodarev). Part IV: Finance and Risk -- Ambit processes, their volatility determination and their applications (Corcuera, Farkas, Valdivia) -- Some functional analytic tools for utility maximization (Gushchin, Khasanov, Morozov) -- Maximization of the survival probability by franchise and deductible amounts in the classical risk model (Ragulina).Part V: Statistics.-Asymptotic properties of drift parameter estimator based on discrete observations of stochastic differential equation driven by fractional Brownian motion ( Mishura, Ralchenko, Seleznev, Shevchenko) -- Minimum contrast method for parameter estimation in the spectral domain (Sakhno) -- Conditional estimators in exponential regression with errors in covariates (Shklyar).

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