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Mathematical bases for stochastic calculus - WMMFMA22

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  • Number of hours

    • Lectures : 18.0
    ECTS : 2.0

Goals

This course aims to provide the foundations of stochastic calculus. We insist on the mathematical aspects of this calculus, its applications to finance also being developed in other modules. The goal is to familiarize students with the language of stochastic analysis, used extensively in research articles in financial mathematics.

Contact Pierre ETORE

Content

1. Overview of random processes: comparison of processes, C and D spaces, continuous time filtration, sigma-algebra of events prior to a stoping time.
2. Martingale: martingale in continuous time, Doob decomposition, local martingales.
3. Itô's integral: quadratic variation of random processes, integration by bounded martingales, Kunita-Watanabe's inequality, integration by local martingale
4. Itô's calculus: integration by semi-martingales, Itô's processes, Itô's formula, applications : SDE solution.
5. Girsanov's theorems : exponential martingale, martingale measure, applications to nondegenerate Brownian diffusions.
6. Stochastic Differential Equations : strong solutions, Itô's Theorem, examples and counter-examples, Applications: Black and Scholes model, weak solutions of SDE.
7. Diffusions and probabilistic interpretation of PDE: Markov property, gernerators, Feynman-Kac formulas



Prerequisites

4MMPSAF Stochastic processes and application in finance (or another equivalent course)

Tests



N1=(2/3)E1+(1/3)CC
N2=E2
N=Max(N1,N2)

CC = Contrôle continu,
E1 = examen écrit,
E2 = examen écrit (session de rattrapage)

Additional Information

Curriculum->Financial Engineering->Semester 9

Bibliography

I. Karatzas, S.E. Shreve "Brownian motion and stochastic calculus", Springer

D. Revuz, M. Yor "Continuous martingales and Brownian Motion", Springer

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Date of update January 15, 2017

Grenoble INP Institut d'ingénierie Univ. Grenoble Alpes