000			02554nam a2200193 4500
020			_a9783031631924
041			_aEnglish
082			_a330.0212 _bPAS/P
084			_2Colon Classification
100			_aPascucci, Andrea
245			_aProbability Theory II : _bStochatic Calculus
250			_a1
260			_aItaly: _bSpringer, _c2024.
300			_a426p.
500			_aThis book offers a modern approach to the theory of continuous-time stochastic processes and stochastic calculus. The content is treated rigorously, comprehensively, and independently. In the first part, the theory of Markov processes and martingales is introduced, with a focus on Brownian motion and the Poisson process. Subsequently, the theory of stochastic integration for continuous semimartingales was developed. A substantial portion is dedicated to stochastic differential equations, the main results of solvability and uniqueness in weak and strong sense, linear stochastic equations, and their relation to deterministic partial differential equations. Each chapter is accompanied by numerous examples. This text stems from over twenty years of teaching experience in stochastic processes and calculus within master's degrees in mathematics, quantitative finance, and postgraduate courses in mathematics for applications and mathematical finance at the University of Bologna. The book provides material for at least two semester-long courses in scientific studies (Mathematics, Physics, Engineering, Statistics, Economics, etc.) and aims to provide a solid background for those interested in the development of stochastic calculus theory and its applications. This text completes the journey started with the first volume of Probability Theory I - Random Variables and Distributions, through a selection of advanced classic topics in stochastic analysis. This book offers a modern approach to the theory of continuous-time stochastic processes and stochastic calculus
505			_a1 Stochastic processes 2 Markov processes 3 Continuous processes 4 Brownian motion 5 Poisson process 6 Stopping times 7 Strong Markov property 8 Continuous martingales 9 Theory of variation 10 Stochastic integral 11 Itô's formula 12 Multidimensional stochastic calculus 13 Change of measure and martingale representation 14 Stochastic differential equations 15 Feynman-Kac formulas 16 Linear stochastic equations 17 Strong solutions 18 Weak solutions 19 Complements.-20 A primer on parabolic PDEs
650			_aEconomics, Probability Theory
942			_2ddc _cREF
999			_c748861 _d748861