Portfolio Management (765N1)
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Portfolio Management
Module 765N1
Module details for 2026/27.
15 credits
FHEQ Level 7 (Masters)
Module Outline
This module provides a comprehensive introduction to the principles and practice of portfolio management, bridging theoretical concepts with real-world applications. It is designed to prepare students for professional roles in the investment and fund management industry.
Working in small teams, students will be given a portfolio management mandate and will design and implement an investment portfolio. They will analyse its performance and prepare a professional report presenting their findings to a client panel simulating an institutional investment setting. This approach helps students develop skills essential for effective portfolio management, including teamwork, communication, and critical analysis.
The module combines lectures, which focus on the theory of asset allocation and portfolio construction, with hands-on seminars that guide students through practical implementation using programming tools including Python and AI-based methods. Topics include passive and active investment strategies, mean–variance analysis, portfolio optimisation, performance evaluation, and the design of specialised strategies such as those used by hedge funds.
Module learning outcomes
Understand the significance of a portfolio management mandate.
Understand and apply standard and advanced portfolio construction techniques for both passive and active portfolio management using risk-adjusted and utility-based performance criteria.
Conduct porftolio risk analysis and performance evaluation with modern information systems such as Bloomberg or Refinitiv, and employ programming tools, including Python, and AI-based methods, where relevant.
Work effectively in a team environment: plan and execute portfolio strategies and critically appraise their outcome.
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 30.00% | |
| Coursework components. Weighted as shown below. | ||
| Group written submission | T2 Week 8 | 100.00% |
| Computer Based Exam | Semester 2 Assessment | 70.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Spring Semester | Lecture | 2 hours | 11111111111 |
| Spring Semester | Workshop | 1 hour | 11111111111 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr Thanos Andrikopoulos
Assess convenor
/profiles/647712
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