Stochastic Calculus: An Introduction Through Theory and Exercises

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Springer, 9 nov 2017 - 627 pagine

This book provides a comprehensive introduction to the theory of stochastic calculus and some of its applications. It is the only textbook on the subject to include more than two hundred exercises with complete solutions.

After explaining the basic elements of probability, the author introduces more advanced topics such as Brownian motion, martingales and Markov processes. The core of the book covers stochastic calculus, including stochastic differential equations, the relationship to partial differential equations, numerical methods and simulation, as well as applications of stochastic processes to finance. The final chapter provides detailed solutions to all exercises, in some cases presenting various solution techniques together with a discussion of advantages and drawbacks of the methods used.

Stochastic Calculus will be particularly useful to advanced undergraduate and graduate students wishing to acquire a solid understanding of the subject through the theory and exercises. Including full mathematical statements and rigorous proofs, this book is completely self-contained and suitable for lecture courses as well as self-study.

 

Sommario

1 Elements of Probability
1
2 Stochastic Processes
31
3 Brownian Motion
45
4 Conditional Probability
85
5 Martingales
108
6 Markov Processes
151
7 The Stochastic Integral
181
8 Stochastic Calculus
214
10 PDE Problems and Diffusions
305
11 Simulation
340
12 Back to Stochastic Calculus
365
Finance
395
Solutions of the Exercises
437
References
622
Index
625
Copyright

9 Stochastic Differential Equations
255

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Informazioni sull'autore (2017)

Paolo Baldi is professor at the Dipartimento di Matematica at the Università di Roma "Tor Vergata". He previously held positions at the universities of Catania and Pisa in Italy and also many visiting positions at the universities of Nanterre and Pierre et Marie Curie (Paris 6) in France. His research focuses on stochastic processes, in particular stochastic modeling on algebraic structures, large deviations and numerical applications.

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