Module Specification

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
1. Module Title Computer-Based Trading in Financial Markets
2. Module Code COMP226
3. Year Session 2023-24
4. Originating Department Computer Science
5. Faculty Fac of Science & Engineering
6. Semester Second Semester
7. CATS Level Level 5 FHEQ
8. CATS Value 15
9. Member of staff with responsibility for the module
Dr Y Wang Computer Science Yongzhao.Wang@liverpool.ac.uk
10. Module Moderator
11. Other Contributing Departments  
12. Other Staff Teaching on this Module
Mrs J Birtall School of Electrical Engineering, Electronics and Computer Science Judith.Birtall@liverpool.ac.uk
Professor RSJ Savani Computer Science Rahul.Savani@liverpool.ac.uk
13. Board of Studies
14. Mode of Delivery
15. Location Main Liverpool City Campus
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
16. Study Hours 30

    10

    40
17.

Private Study

110
18.

TOTAL HOURS

150
 
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other
19. Timetable (if known)            
 
20. Pre-requisites before taking this module (other modules and/or general educational/academic requirements):

COMP116 Analytic Techniques for Computer Science
21. Modules for which this module is a pre-requisite:

 
22. Co-requisite modules:

 
23. Linked Modules:

 
24. Programme(s) (including Year of Study) to which this module is available on a mandatory basis:

25. Programme(s) (including Year of Study) to which this module is available on a required basis:

26. Programme(s) (including Year of Study) to which this module is available on an optional basis:

27. Aims
 

To develop an understanding of financial markets at the level of individual trades. To provide an overview of the range of different computer-based trading applications and techniques. To introduce the key issues with using historical high-frequency financial data for developing computer-based trading strategies. To provide an overview of statistical and computational methods for the design of trading strategies and their risk management. To develop a practical understanding of the design, implementation, evaluation, and deployment of trading strategies.

 
28. Learning Outcomes
 

(LO1) Have an understanding of market microstructure and its impact on trading.

 

(LO2) Understand the spectrum of computer-based trading applications and techniques, from profit-seeking trading strategies to execution algorithms.

 

(LO3) Be able to design trading strategies and evaluate critically their historical performance and robustness.

 

(LO4) Understand the common pitfalls in developing trading strategies with historical data.

 

(LO5) Understand the benchmarks used to evaluate execution algorithms.

 

(LO6) Understand methods for measuring risk and diversification at the portfolio level.

 

(S1) Self-management (Readiness to accept responsibility (i.e. leadership), flexibility, resilience, self-starting, appropriate assertiveness, time management, readiness to improve own performance based on feedback/reflective learning.)

 

(S2) Application of numeracy (Manipulation of numbers, general mathematical awareness and its application in practical contexts (e.g. measuring, weighing, estimating and applying formulae).)

 

(S3) Problem solving (Analysing facts and situations and applying creative thinking to develop appropriate solutions.)

 

(S4) Application of information technology (Basic IT skills, including familiarity with word processing, spreadsheets, file management and use of internet search engines.)

 

(S5) Computer Science principles

 

(S6) Computer Science practice

 
29. Teaching and Learning Strategies
 

Teaching Method 1 - Lecture
Description:
Teaching Method 2 - Laboratory Work
Description:

Standard on-campus delivery
Teaching Method 1 - Lecture
Description: Mix of on-campus/on-line synchronous/asynchronous sessions
Teaching Method 2 - Laboratory Work
Description: On-campus synchronous sessions

 
30. Syllabus
   

Introduction and overview of the module (1 Lecture).
An overview of financial markets and instruments (2 Lectures).
Using R for financial modelling (2 Lectures and 2 Practicals).
Market microstructure, the limit order book, and dark pools of liquidity (2 Lectures and 1 Tutorial).
Profit seeking versus execution algorithms (1 Lecture).
Designing and testing trading strategies (4 Lectures and 1 Practical).
Common pitfalls when using historical data for developing trading strategies (2 Lectures and 1 Practical).
Statistical tests for evaluating trading strategies (3 Lectures and 1 Tutorial).
Money management techniques (2 Lectures and 1 Practical).
Price benchmarks for execution algorithms (2 Lectures and 1 Tutorial).
A selection of advanced topics: e.g. Smart order routing; Statistical arbitrage (5 Lectures and 1 Practical/Tutorial).
A guide to trading strategy project work (4 Lectures and 1 Practical).

 
31. Recommended Texts
  Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.
 

Assessment

32. EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (226) Written exam There is a resit opportunity. Assessment Schedule (When) :2 120 80
33. CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (226.1) Assessment 1 Standard UoL penalty applies for late submission. This is not an anonymous assessment. 0 10
  (226.2) Assessment 2 Standard UoL penalty applies for late submission. This is not an anonymous assessment. 0 10