STAT40680 Stochastic Models

Academic Year 2022/2023

This module covers part of the syllabus for the professional examination, Models (CS2), of the Faculty and Institute of Actuaries (UK) and is twinned with the module, Models - Survival Models. The module treats the principles behind, and key characteristics, of stochastic models in actuarial applications. Topics treated include: introduction to stochastic modelling; conditional expectation and conditional distribution, martingales, random walks, Markov chains with actuarial applications, continuous time Markov processes, Brownian motion with applications to mathematical finance, Poisson processes.

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Curricular information is subject to change

Learning Outcomes:

The student will be able to define and classify stochastic models, judge when a model is satisfactory and be able to outline how to construct a stochastic model. The student will be able to apply Markov chains and Markov jump processes to actuarial applications, solving for their short run and long run behaviour. The student will be able to calibrate models from data, test the appropriateness of models, judge their overall suitability and simulate their behaviour.

Indicative Module Content:

Student Effort Hours: 
Student Effort Type Hours




Autonomous Student Learning




Approaches to Teaching and Learning:
Lectures, tutorials, enquiry and problem-based learning. 
Requirements, Exclusions and Recommendations
Learning Requirements:

The student will have an aptitude for mathematics, with a profligacy to 1st years honours level, and have taken level 2 modules in statistics.

Learning Recommendations:

Knowledge of probability theory and basic statistics to the level of the Probability Theory (STAT20110) and Inferential Statistics (STAT20100) course. Good knowledge in calculus (integrals, differentials) and linear algebra (vectors, matrices, eigenvalues).

Module Requisites and Incompatibles
STAT40210 - Stochastic Models

Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Examination: Mid-term exam Week 7 No Alternative linear conversion grade scale 40% No


Examination: Final Examination 2 hour End of Trimester Exam No Alternative linear conversion grade scale 40% No


Carry forward of passed components
Resit In Terminal Exam
Spring Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Mr Matt Nagle Tutor
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Lecture Offering 1 Week(s) - Autumn: All Weeks Fri 14:00 - 15:50
Tutorial Offering 1 Week(s) - 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 Thurs 15:00 - 15:50