MSc Algorithmic Trading

On our MSc Algorithmic Trading, we equip you with the core concepts and quantitative methods in high frequency finance, along with the operational skills to use state-of-the-art computational methods for financial modelling.

We enable you to attain an understanding of financial markets at the level of individual trades occurring over sub-millisecond timescales, and apply this to the development of real-time approaches to trading and risk-management.

The course includes hands-on projects on topics such as order book analysis, VWAP & TWAP, pairs trading, statistical arbitrage, and market impact functions. You have the opportunity to study the use of financial market simulators for stress testing trading strategies, and designing electronic trading platforms.

In addition to traditional topics in financial econometrics and market microstructure theory, we put special emphasis on areas:

  • Statistical and computational methods
  • Modelling trading strategies and predictive services that are deployed by hedge funds
  • Algorithmic trading groups
  • Derivatives desks
  • Risk management departments

Our Centre for Computational Finance and Economic Agents is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation. We are supported by Essex’s highly rated Department of Economics, School of Computer Science and Electronic Engineering, and Essex Business School. That's why we are ranked 6th in the UK for research power in computer science (Times Higher Education research power measure, Research Excellence Framework 2021).

This course is available to study part-time.

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Modules

  • Compulsory modules
  • CCFEA MSc Dissertation
  • Big-Data for Computational Finance
  • Introduction to Financial Market Analysis
  • Quantitative Methods in Finance and Trading
  • Computational Models in Economics and Finance
  • Computational Market Microstructure for FinTech and the Digital Economy
  • Professional Practice and Research Methodology
  • Options modules
  • Introduction to Programming in Python
  • Text Analytics
  • Mathematical Research Techniques Using Matlab
  • Financial Engineering and Risk Management
  • Industry Expert Lectures in Finance
  • £22,400 Per Year

    International student tuition fee

    1 Year

    Duration

    Oct 2024

    Start Month

    Sep 2024

    Application Deadline

    Upcoming Intakes

    • October 2024
    • October 2025

    Mode of Study

    • Full Time