Module Details

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.
Title COMPUTER-BASED TRADING IN FINANCIAL MARKETS
Code COMP226
Coordinator Dr RSJ Savani
Computer Science
Rahul.Savani@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2016-17 Level 5 FHEQ Second Semester 15

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.

Learning Outcomes

At the end of the module students will be expected to:

  • Have an understanding of market microstructure and its impact on trading.
  • Understand the spectrum of computer-based trading applications and techniques, from profit-seeking trading strategies to execution algorithms.
  • Be able to design trading strategies and evaluate critically their historical performance and robustness.
  • Understand the common pitfalls in developing trading strategies with historical data.
  • Understand the benchmarks used to evaluate execution algorithms.
  • Understand methods for measuring risk and diversification at the portfolio level.

Syllabus

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


Teaching and Learning Strategies

Lecture -

Laboratory Work -


Teaching Schedule

  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 30

    10

    40
Timetable (if known)              
Private Study 110
TOTAL HOURS 150

Assessment

EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
Written Exam  2 hours  80  August/September  N/A  Assessment 3 Notes (applying to all assessments) Programming assignment Students will be required to implement a solution for a trading problem. This work is not marked anonymously. Resit-arrangements: Each resit assessment task will be the same or very similar to the original task, but on a different dataset. The deadline for the submission of work for each resit assessment task will be set by the module coordinator and will be part of the description of the assessment task; the deadline will typically fall within the resit period; the description of a resit assessment task will be provided at least four weeks before the deadline for the submission of work for the the task. Trading strategy design and evaluation Students will be required to design and implement a trading strategy, test it on historical data, and produce a report detailing their work. This work is not marked anonymously. Resit arrangements: Identical to those for the Programming assignment. Written Examination  
CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
Coursework  12 hours expected  10  Within current academic year  According to University policy  Assessment 1 
Coursework  12 hours expected  10  Within current academic year  According to University policy.  Assessment 2 

Recommended Texts

Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.
Explanation of Reading List: