Aims

1. To give students the opportunity to work in a team to explore in depth the problem of automated trading from a practical perspective.
2. To provide experience of working in a team.
3. To provide experience of all aspects of solving a substantial problem, including the production of a final report.
4. To enhance communication skills, both oral and written.

Syllabus

All projects should contain the following elements: research, design, realisation and evaluation.

Recommended Texts

• C. W. Dawson: Essence of computing projects: a student`s guide. Prentice Hall (most recent edition).
• W. N. Venebles, D. M. Smith, and the R development team: An Introduction to R. Available electronically from http://cran.r-project.org/doc/manuals/R-intro.pdf.

Learning Outcomes

At the end of this module students should be able to

1. work effectively and cooperatively as part of a team while taking on a range of different roles within the team;
2. plan, manage, and execute the project as a group within the time available while managing their individual time effectively so as to carry out the group's plan;
3. design and implement trading strategies and evaluate critically their performance and robustness;
4. locate and make use of information relevant to their project;
5. prepare and deliver a formal presentation showing practical competence and demonstrating aspects of the project;
6. document the work conducted in the project in a final report.

Learning Strategy

Background: In the project we wish to foster both self and peer guided learning and team work, under the guidance of a supervisor. Students are divided into teams of five, and each team is expected to work largely autonomously on the design of automated trading strategies. The trading strategies of the students will be evaluated in a competition, and the performance of the trading strategies will contribute towards the final mark of the students.The students will do their research and development within the R statistical computing language ( www.r-project.org). Financial data will be made available. Via lectures and practicals, students will be introduced to relevant packages within R, along with tools and techniques for their projects.

Formal Lectures and Practicals: Students will be expected to attend five hours of formal lectures and five practicals. The lectures will cover:

• Background information on automated trading.
• The design of trading strategies.
• The optimization and evaluation of trading strategies.
• The format of assessment and feedback within the module.
• Report writing and presentation skills.

Teamwork and Supervision: Teams will be allocated a first and second supervisor and will hold regular meetings with their supervisors. Teams will be expected to hold regular project meetings. The minutes of these meeting will be monitored by the supervisor of the team, who will intervene if there are problems.

Assessment: Projects are assessed at the following three points:

1. Design (oral presentation + documentation, week 8-10)
2. Evaluation of trading strategies (submitted code, week 18)
3. Final report (written, week 24)

The final report will be written by the whole team. In addition each individual team member will submit a peer review containing a reflection on the individual's own performance and that of the other team members. The mark for the final report will be used in conjunction with the individually submitted peer reviews to arrive at individual mark for each team member.