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ICM325 - Algorithmic and High Frequency Trading

ICM325-Algorithmic and High Frequency Trading

Module Provider: ICMA Centre
Number of credits: 10 [5 ECTS credits]
Level:7
Terms in which taught: Summer term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2021/2

Module Convenor: Dr Alfonso Dufour
Email: a.dufour@icmacentre.ac.uk

Type of module:

Summary module description:

Industry participants estimate that 70-80% of equity trades are executed through computers. Market-makers in fixed income and currency markets use algorithms to automatically adjust their quotes. This module reviews the current state of the trading industry and identifies aims, features, regulations, and limitations of three main groups of algorithmic trading strategies: market making, trade execution and statistical arbitrage. Practical seminars are used to demonstrate how to apply trading algorithms to high-frequency data.


Aims:

Equip the students with a basic knowledge of algorithmic and high frequency trading strategies. 


Assessable learning outcomes:

By the end of the module, it is expected that the student will be able to:




  • explain the concepts of high frequency trading and algorithmic trading

  • identify the characteristic elements of alternative algorithmic trading strategies

  • solve simple trade execution problems and develop effective execution strategies


Additional outcomes:

The module will offer the opportunity to develop tick-by-tick data management skills, learn how to use Pivot Tables and Solver in excel and acquire basic programming skills.


Outline content:

Lecture 1 – Algorithmic Trading

Evolution of automated trading; Automated orders (pegged orders, iceberg orders); Market making algorithms; Algorithms to execute large trades; Automatic trading decisions (statistical arbitrage); and Future trends (electronic executions for baskets of assets). 

Workshop 1: Insights for working with high-frequency data – features, seasonality, relevant variables, trends and common patterns.



Lecture 2 - HFT

High frequency trading firms are the new market makers. HFT regulation (roles and obligations). Market-making. Main HFT firms (Virtu Financial, Citadel Securities, Two Sigma Securities, etc.) and their strategies.

Workshop 2: Insights for developing auto quoting systems.



Lecture 3 – Algorithmic Execution Strategies

Overview of popular trade execution algorithms: VWAP, TWAP, Volu me in line (participation), Liquidity seekers (Tex, Guerrilla, etc.) and Optimal trade execution.

Workshop 3: Trading risk vs. impact cost: Using solver in Excel to optimise trade executions.



Lecture 4 – VWAP Execution and performance measurement

Developing and implementing the VWAP execution strategy: naïve VWAP vs. smart VWAP. Reviewing ITG VWAP strategy. 

Workshop 4: executing VWAP trades using Pivot Tabl es in Excel.



Lecture 5 - Technical Analysis and Statistical Arbitrage Trades

Introduction to technical analysis. Developing a trading strategy with automatic trading decisions. Assessing the performance of the strategy.

Workshop 5: executing a statistical arbitrage trade. 



Lecture 6 – Revision


Global context:

Examples from and applications to international markets


Brief description of teaching and learning methods:

Lectures with presentation and discussion of concepts and real-world examples. Workshops with practical applications to financial data.


Contact hours:
  Autumn Spring Summer
Lectures 12
Seminars 10
Guided independent study:      
    Wider reading (independent) 30
    Wider reading (directed) 8
    Exam revision/preparation 14
    Preparation for seminars 3
    Revision and preparation 15
    Reflection 8
       
Total hours by term 0 0 100
       
Total hours for module 100

Summative Assessment Methods:
Method Percentage
Project output other than dissertation 70
Class test administered by School 30

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

1-hour multiple choice-test (30%)

Group project (70%)


Formative assessment methods:

Sample multiple-choice questions and seminar discussion. 


Penalties for late submission:

Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information: http://www.reading.ac.uk/internal/exams/student/exa-guidePG.aspx


Assessment requirements for a pass:

50% weighted average mark.


Reassessment arrangements:

Re-submit project only.


Additional Costs (specified where applicable):

Last updated: 8 April 2021

THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.

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