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
David Mendes Duarte
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
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
- Electronic Trading in Financial Markets
- Basic Concepts, Characteristics and Methodologies
- Types of Assets and Orders
- Market Terminology
- Microstructure of Financial Markets
- Fundamentals
- Participants and Liquidity Providers
- Execution of Orders
- Market Efficiency
- The Relevance of Technical Analysis
- 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
- Impact of Regulation in Algorithmic Trading
- Quality of Data
- Transparency and Disclosure
- Transaction Cost Analysis
- Reporting
- Associated Risks
- Case Studies