ST303 Half Unit
Stochastic Simulation
This information is for the 2020/21 session.
Teacher responsible
Angelos Dassios
Availability
This course is available on the BSc in Actuarial Science and BSc in Mathematics, Statistics and Business. This course is not available as an outside option nor to General Course students.
Course capped at 60.
Pre-requisites
Students must have completed:
EITHER Probability, Distribution Theory and Inference (ST202) OR Probability and Distribution Theory (ST206)
AND Stochastic Processes (ST302).
While the course ST306 is not a formal pre-requisite some examples from this course will be used. Students that have not taken ST306 might have to do a bit of extra reading to familiarise themselves with them.
Course content
An introduction to using R for stochastic simulation as well as methods of simulating random variables, complicated quantities involving several random variables and paths of stochastic processes. Applications will focus on examples from insurance and finance.
Teaching
This course will be delivered through a combination of classes and lectures totalling a minimum of 30 hours in the Lent Term. This year, some or all of this teaching may be delivered through a combination of virtual classes and flipped-lectures delivered as short online videos.
Formative coursework
Weekly exercises usually involving computing.
Indicative reading
- Introducing Monte Carlo methods with R (main reference), by G. Robert and G. Casella.
Useful reading:
- Stochastic Simulation, Algorithms and Analysis by S. Asmussen.
- Monte Carlo Methods in Financial Engineering by P. Glasserman.
Assessment
Project (35%) in the LT.
Project (65%) in the ST.
Student performance results
(2017/18 - 2019/20 combined)
| Classification | % of students |
|---|---|
| First | 58.6 |
| 2:1 | 24.3 |
| 2:2 | 9.2 |
| Third | 4.6 |
| Fail | 3.3 |
Important information in response to COVID-19
Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Key facts
Department: Statistics
Total students 2019/20: 42
Average class size 2019/20: 21
Capped 2019/20: Yes (60)
Value: Half Unit
Personal development skills
- Self-management
- Team working
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills
- Specialist skills
