The "Investments & Portfolio Management" course offers an in-depth examination of modern investment practices, quantitative portfolio management, and risk analysis. Building on foundational concepts, students will master portfolio design and management, predictive analytics, trading strategies, portfolio resilience, performance attribution and risk management strategies in complex market environments.

A unique feature of this course is its integration of Bloomberg Labs, where students can access real-time financial data, utilize advanced modelling tools, and engage in portfolio simulations. This hands-on experience with industry-standard software empowers students to construct and analyse portfolios in ways that reflect real-world practices in investment management, enhancing their data-driven decision-making abilities.

Key topics include introduction to advanced financial markets and investment landscape, quantitative methods in finance, advanced portfolio theory and optimisation including factor investing and smart beta, term structure models and fixed income strategies, equity and valuation techniques and portfolio analysis and attribution.

Students will further explore theoretical foundations and empirical evidence behind strategies such as value and momentum investing, while also assessing market efficiency, behavioural biases, and risk factors.

This course emphasizes experiential learning in various ways (i.e. The FT Article of the Week), fostering analytical, problem-solving, and critical thinking skills. Through collaborative group projects, students will simulate professional environments, where interdisciplinary and global perspectives are vital. Peer-learning activities and case-based discussions enable students to approach investment challenges from diverse viewpoints, cultivating adaptability and a strategic mindset for high-level careers in investment analysis, asset management, and financial technology (FinTech). 

A 2-hour weekly lecture for 10 weeks

Three 1-hour Bloomberg sessions

Two 1-hour computer labs.
One 2-hour revision lecture.

None

This course aims to

■ Develop advanced analytical and quantitative skills to design investment strategies and evaluate market behaviour.

■ Enable mastery of international portfolio management, optimize portfolio resilience, performance attribution and risk management strategies in complex market environments.

■ Foster advanced critical thinking on market theories and investment strategies, cultivating an informed perspective on market inefficiencies and opportunities for strategic asset allocation and alpha generation.

By the end of the course, students should be able to:

1. Critically analyse theoretical foundations and empirical evidence and investigating economic behaviour under uncertainty.

2. Design efficient resilient portfolios of various assets and develop portfolio diversification strategies for different risk tolerances, utilizing portfolio performance metrics, attribution models, and risk-adjusted returns in investment decision-making.

3. Evaluate market theories to identify empirical anomalies and behavioural patterns that support strategic asset allocation and alpha generation.

4. Integrate financial technology to drive data-driven investment decisions, utilising Bloomberg Terminal and the mastery of advanced financial tools.

5. Collaborate and produce a comprehensive team-based project, demonstrating group decision-making, synthesis of diverse perspectives, and co-authorship of a combined piece of coursework.

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.