FINN40415

Postgraduate Programmes 2023/24

SUMMATIVE ASSIGNMENT – FINN40415

PORTFOLIO MANAGEMENT

DeMiguel, Garlappi and Uppal (2007) reveal that the naive diversification, the 1/N rule, or equally weighted portfolio is generally no worse than many more sophisticated strategies suggesting that “there are still many miles to go before the gains promised by optimal portfolio choice can actually be realized out of sample."

The objective of this assignment is to understand why optimal portfolios are not well performing particularly when compared against the equally weighted portfolio and learn how academics and practitioners have been addressing this issue. By replicating some of the portfolio models, students will have an opportunity to practise Matlab and understand potential issues that might arise during implementation.

Students are encouraged to use Matlab for empirical analysis.

The report must follow the structure:

1. Introduction (5%)

Give a brief introduction and overview of your report.

2. Literature Review (40%)

Conduct a review of research articles that have employed models of portfolio optimisation and provide a detailed summary of each study. The review can include key elements such as the adopted portfolio models, objective functions, datasets and samples, performance evaluation methods, and the findings and implications of each study.

· Summarise the aims and objectives addressed in each paper (5%)

· Clearly outline the portfolio models, including the mathematical derivation of the proposed objective functions and any relevant constraints (10%)

· Discuss the datasets and samples utilised in each study, and their relevance to portfolio modelling. Include details on the types of financial instruments or assets included, time periods covered, and any specific market conditions considered (10%)

· Describe the methodologies employed for evaluation of the performance of portfolio models. This could include measures like Sharpe ratio, Maximum Drawdown, or other risk-adjusted performance metrics (5%)

· Present the key findings and implications of each paper related to the adopted portfolio models (10%)

The report should have an easy structure to follow. A focused review on a small number of papers is preferred to a brief review of many papers.

3. Empirical Analysis (40%)

Choose one paper and replicate it using a different dataset. The dataset will be uploaded in Ultra in due course. You can also use other relevant datasets from reliable sources. If the paper contains several models, choose one for replication.

o Provide a description of the model with implementation details such as model derivation, specific objective functions, constraints, etc.

o Evaluate the model using the dataset. Evaluation should include comparison with the equally-weight portfolio as a benchmark. Use relevant performance metrics such as risk-adjusted returns, Sharpe ratio, and maximum drawdown, etc. Provide details about your specific Matlab code or program in the appendix of your report for transparency and verification.

o Analyse and discuss the outcomes of your replication. Compare your results with the results presented in the original paper, and provide a critical evaluation.

4. Conclusion (15%)

Reflect on your findings and provide your view on the effectiveness of optimal portfolio models. Are we better off with the equally-weight portfolio?

Overall word limit: 2500 WORDS MAXIMUM

SUBMISSION INSTRUCTIONS

Assignments should be typed, using 1.5 spacing and an easy-to-read 12-point font. Assignments and dissertations/business projects must not exceed the word count indicated in the module handbook/assessment brief.

The word count should:

▪ Include all the text, including title, preface, introduction, in-text citations, quotations, footnotes, and any other items not specifically excluded below.

▪ Exclude diagrams, tables (including tables/lists of contents and figures), equations, executive summary/abstract, acknowledgements, declaration, bibliography/list of references and appendices. However, it is not appropriate to use diagrams or tables merely as a way of circumventing the word limit. If a student uses a table or figure as a means of presenting his/her own words, then this is included in the word count.

Examiners will stop reading once the word limit has been reached, and work beyond this point will not be assessed. Checks of word counts will be carried out on submitted work, including any assignments or dissertations/business projects that appear to be clearly over-length. Checks may take place manually and/or with the aid of the word count provided via an electronic submission. Where a student has intentionally misrepresented their word count, the school may treat this as an offence under Section IV of the General Regulations of the University. Extreme cases may be viewed as dishonest practice under Section IV, 5 (a) (x) of the General Regulations.

Very occasionally it may be appropriate to present, in an appendix, material which does not properly belong in the main body of the assessment but which some students wish to provide for the sake of completeness. Any appendices will not have a role in the assessment - examiners are under no obligation to read appendices and they do not form part of the word count. Material that students wish to be assessed should always be included in the main body of the text.

Guidance on referencing can be found in the programme handbook and on ULTRA.

MARKING GUIDELINES

Performance in the summative assessment for this module is judged against the following criteria:

• Relevance to question(s)

• Organisation, structure and presentation

• Depth of understanding

• Analysis and discussion

• Use of sources and referencing

• Overall conclusions

The word count should include all the text (plus endnotes and footnotes), but exclude diagrams, tables, bibliography, references and appendices. Guidance on referencing can be found in your Assessment handbook under ‘Things you Need to Know’ on Sharepoint.