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Stochastic Analysis

Key information

  • Module code:

    7CCMFM04

  • Level:

    7

  • Semester:

      Spring

  • Credit value:

    15

Module description

Syllabus

Normal random variables and Gaussian processes; martingales; Brownian motion, stochastic integral, rules for stochastic calculus (Ito, martingale representation, Levy characterisation);applications: stochastic differential equations; martingale representation and Girsanov's change of measure.

Prerequisites

7CCMFM01, real analysis, basic probability theory.

 

Assessment details

Assessment

2 hr written examination, class test, or alternative assessment

Educational aims & objectives

Aims

You will acquire a sophisticated understanding of several modern concepts and results in the theory of stochastic processes, including stochastic calculus and the theory of Brownian motion.

Teaching pattern

Four hours of lectures, 1 tutorial and 2 walk-in tutorials per week for the second half of Semester.

Suggested reading list

Suggested reading/resource (link to My Reading Lists)

Department

Module description disclaimer

King’s College London reviews the modules offered on a regular basis to provide up-to-date, innovative and relevant programmes of study. Therefore, modules offered may change. We suggest you keep an eye on the course finder on our website for updates.

Please note that modules with a practical component will be capped due to educational requirements, which may mean that we cannot guarantee a place to all students who elect to study this module.

Please note that the module descriptions above are related to the current academic year and are subject to change.