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Durham University

Postgraduate Module Handbook 2021/2022

Archive Module Description

This page is for the academic year 2021-22. The current handbook year is 2022-23

Department: Computer Science

COMP52415: Financial Technology: Algorithmic Trading and Market Making in Options

Type Tied Level 5 Credits 15 Availability Available in 2021/22
Tied to G5K609 Scientific Computing and Data Analysis [Final intake in October 2022]

Prerequisites

  • None

Corequisites

  • None

Excluded Combination of Modules

  • None

Aims

  • Develop knowledge of key concepts and issues in finance theory related to asset valuation, portfolio management and derivative pricing
  • Develop critical understanding and appreciation of current theoretical and empirical research in financial theory and its applications to professional practice.

Content

  • Trading and Financial Markets
  • Data Acquisition, Processing and Analysis in Financial Marking
  • Trading algorithms and risk management
  • Options prizing, volatility
  • Market making and market crashes

Learning Outcomes

Subject-specific Knowledge:
  • Developed a critical understanding of the equilibrium concepts and arbitrage relationship used in the pricing of derivatives instruments
  • Developed an advanced knowledge of the principles and practice of analysing market data and defining a trading strategy in financial instruments
  • Developed a good understanding of managing the risks of a trading strategy and the resulting portfolio
  • Explored the most recent advancements in the relevant academic literature and devloped a critical understanding of their implications for current professional practice.
Subject-specific Skills:
  • By the end of the module, students should have developed highly specialised and advanced technical, professional and academic skills that enable them to:
  • formulate and solve problems in analysing data and defining trading strategies
  • develop trading strategies and use appropriate models to trade, manage risk and evaluate performance.
Key Skills:
  • Organisation, time management, initiative, adaptability
  • Problem analysis and solving, numeracy, computer literacy
  • Presentation in oral and written form.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Teaching will be by lectures and workshops
  • The lectures provide the means to give a concise, focused presentation of the subject matter of the module.
  • When appropriate, the lectures will aslo be supported by the distribution of written material, or by information and relevant links on DUO.
  • Regular problem exercises and workshops will give students the chance to develop their theoretical understanding and problem solving skills.
  • Students will be able to obtain further help in their studies by approaching their lecturers, either after lectures or at other mutually convenient times.
  • Student performance will be summatively assessed through coursework.
  • The formative coursework provides opportunities for feedback, for students to gauge their progress and for staff to monitor progress throughout the duration of the module.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Lectures 16 4 per week 1 hour 16
Practical Classes 16 4 per week 1 hour 16
Self-study 68
Total 150

Summative Assessment

Component: Coursework Component Weighting: 100%
Element Length / duration Element Weighting Resit Opportunity
Trading Coursework 100%

Formative Assessment:

Feedback on coursework


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University