Programme And Module Handbook
 
Course Details in 2022/23 Session


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Module Title LM Stochastic Processes
SchoolMathematics
Department Mathematics
Module Code 06 37788
Module Lead
Level Masters Level
Credits 20
Semester Semester 1
Pre-requisites
Co-requisites
Restrictions None
Exclusions
Description This module forms an introduction to Stochastic Processes. While students will be exposed to the relative mathematical theorems there will be an emphasis on the understanding of the relevant definitions and on the application of the underlying results. The module begins with a thorough introduction to the properties of Stochastic processes, followed by a discussion of Markov processes, discrete and continuous Martingales, Brownian Motion and Gaussian process. Stochastic Calculus is introduced and Ito's formula is used to derive the Black Scholes Equation of mathematical finance.
Learning Outcomes By the end of the module students should be able to:
  • By the end of the module students should be able to:Explain the key features of stochastic processes and demonstrate a strong understanding of Markov processes.
  • Understand and explore both discrete and continuous Martingales
  • Model processes governed by Brownian Motion and Gaussian process
  • Perform applications from Stochastic Calculus including the derivation of the Black Scholes Equations.
Assessment 37788-01 : Raw Module Mark : Coursework (100%)
Assessment Methods & Exceptions Assessment:

20%: In-course assessment
80%: 3 hour on-campus examination.

Reassessment:

Students will be allowed a second and final attempt at the final examination during the Supplementary Examination Period with their final mark capped at the pass level of 50%.
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