This module will provide students with a core understanding of algorithmic trading, and specifically how to develop and implement quantitative trading strategies. The module will cover the following indicative topics
• High-frequency trading and tick data
• Backtesting and automated execution
• Mean reversion strategies
• Momentum strategies
• Arbitrage strategies
• Risk management
• Performance evaluation
• Total contact hours: 35
• Private study hours: 115
• Total study hours: 150
Main assessment methods:
Individual report - 1,500 words (30%)
Individual research project – 3,000 words (70%)
Reassessment methods:
Individual research project (100%)
E. Chan, "Algorithmic Trading: Winning Strategies and their Rationale", 2013, Wiley, ISBN: 9781118746912
I. Aldridge, “High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems”, 2009, Wiley, ISBN: 9780470579770
P. Kaufman, “A Guide to Creating a Successful Algorithmic Trading Strategy”, 2016, Wiley, ISBN: 9781119224754
The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
- Demonstrate knowledge and understanding of the advanced concepts and theory within the field of finance and financial technology, and their application to a company's financial decisions
- Apply the research methodologies required to test and evaluate complex finance models
- Demonstrate an in-depth knowledge and understanding of theoretical and practical aspects of algorithmic trading in financial markets
- Demonstrate knowledge and understanding of up-to-date empirical literature in the fields of algorithmic trading and investing
- Apply complex quantitative and statistical methods on financial data
The intended generic learning outcomes.
On successfully completing the module students will be able to:
- Interpret complex financial data and perform quantitative analysis
- Interpret and systematically evaluate the results obtained from quantitative analysis
- Demonstrate and apply in-depth problem-solving skills
- Analyse complex issues relevant to companies' financial decisions
- Conduct systematic research in the area of finance and financial technology
University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer.
