Математические модели стохастической динамики развития предприятий
DOI10.14498/vsgtu1700zbMath1474.91239OpenAlexW3047112947MaRDI QIDQ3387850
L. A. Saraev, Aleksandr Leonidovich Saraev
Publication date: 14 January 2021
Published in: Вестник Самарского государственного технического университета. Серия «Физико-математические науки» (Search for Journal in Brave)
Full work available at URL: http://mathnet.ru/eng/vsgtu1700
stochastic equationsWiener processproduction functiondrift coefficientEuler-Maruyama methodproduction factorsvolatility factor
Applications of stochastic analysis (to PDEs, etc.) (60H30) Financial applications of other theories (91G80) Corporate finance (dividends, real options, etc.) (91G50)
Related Items (3)
Cites Work
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- Noise-induced drift in stochastic differential equations with arbitrary friction and diffusion in the Smoluchowski-Kramers limit
- Weak error for stable driven stochastic differential equations: expansion of the densities
- On the weak approximation of a skew diffusion by an Euler-type scheme
- The law of the Euler scheme for stochastic differential equations. I: Convergence rate of the distribution function
- Classification of stochastic Runge-Kutta methods for the weak approximation of stochastic differential equations
- Weak error for the Euler scheme approximation of diffusions with non-smooth coefficients
- Stochastic Analysis and Diffusion Processes
- Modeling with Itô Stochastic Differential Equations
- The Law of the Euler Scheme for Stochastic Differential Equations: II. Convergence Rate of the Density
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