Algorithmic Trading & Market Microstructure

Objectives

The course seeks to detail and characterise how algorithms are being applied in trading for financial markets products through electronic and automated tools/venues. Given the impact of these high frequency trading patterns in todays markets, the course will also detail the microstructure of financial markets which is essential for the development of these new techniques applied by market participants. The course will also describe some case studies so students can understand their practical application.

General characterization

Code

400109

Credits

2.5

Responsible teacher

Rui Jorge Guimarães Canas Correia

Hours

Weekly - Available soon

Total - Available soon

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English

Prerequisites

Registration in Postgradute of Data Science for Finance.

Bibliography

I. RECOMMENDED

Barry Johnson (2010), Algorithmic Trading and DMA: An introduction to direct access trading strategies, 4Myeloma Press

Zeyu Zheng (2017), Algorithmic Trading: Concepts, Perspectives, and Technical Notes, CreateSpace Independent Publishing Platform

Charles-Albert Lehalle e Sophie Laruelle (2018), Market Microstructure In Practice (Second Edition), World Scientific Publishing Company

Álvaro Cartea, Sebastian Jaimungal, José Penalva (2015), Algorithmic and High-Frequency Trading, Cambridge University Press; 3rd printing 2017 edition

Michael Lewis (2015), Flash Boys, Penguin

 

II. COMPLEMENTAR

Ernest P. Chan (2013), Algorithmic Trading: Winning Strategies and Their Rationale, John Wiley & Sons

 

III. LEGISLATION

European Union MiFID II/MiFIR (Markets in Financial Instruments Directive II/Markets in Financial Instruments Regulation)

 

IV. LINKS

https://www.esma.europa.eu/policy-rules/mifid-ii-and-mifir

Teaching method

  • Expositional and Questioning with Active Methods and Case Studies
  • Investigation Projects and Practical Applications
  • Knowledge Development and Learning Capability

Evaluation method

  • Group Work Assignments (40% of final grade)
  • Individual Final Written Exam (60% of final grade, with a minimum grade of 8/20)

Subject matter

  1. Electronic Trading in Financial Markets
    • Basic Concepts, Characteristics and Methodologies
    • Types of Assets and Orders
    • Market Terminology
  2. Microstructure of Financial Markets
    • Fundamentals
    • Participants and Liquidity Providers
    • Execution of Orders
    • Market Efficiency
    • The Relevance of Technical Analysis
  3. High Frequency Algorithmic Trading
    • Basic Concepts and Overview
    • Types of Algorithms
    • Techniques for Algorithmic Trade Execution
    • The Value of a Microsecond
    • The Potential Impact of Blockchain/DLT Technology
  4. Impact of Regulation in Algorithmic Trading
    • Quality of Data
    • Transparency and Disclosure
    • Transaction Cost Analysis
    • Reporting
    • Associated Risks
  5. Case Studies

Programs

Programs where the course is taught: