This assignment requires you to devise an equity market investment strategy and to use real past data for backtesting this strategy. The strategy can be in any European equity market(s) and can involve an international portfolio. The strategy must be based on fundamental analysis not technical analysis. The backtesting must be implemented in Excel and the electronic file will be part of the submission. In terms of structuring the written assignment, you should envisage a scenario of writing a report to make recommendations to a senior portfolio manager.

The written document has a word limit of 1,000 words (+/- 10%). It must comprise (i) a very brief introduction; (ii) a detailed explanation of the rationale for the strategy; (iii) an analysis of the results of the backtesting; (iv) a focused conclusion. The work can be completed individually or in a group of two. Larger groups are not permitted. The deadline is Wednesday 21st April 2021.

You are free to choose any equity investment strategy, but some possible topical approaches to frame the portfolio formation might involve environmental, social and governance (ESG) factors, financial technology, or international politics and trade.

A suggested timeline for your work is:

– January-February: Reading widely to develop ideas.

– February: Decide on the strategy and complete the data collection.

– March: Implementation of the backtesting in Excel and analysis of the results.

– March and April: Preparing the Excel file for submission. Finalising the report document.

In terms of quantitative techniques, you should utilize your studies in the pre-requisite module ASB2217/3217 (‘Investment’). For example, within that module, you studied arithmetic and logarithmic returns, portfolio returns, standard deviation of returns and covariance of returns. You will be applying these techniques on past data i.e. not using expected returns. You will need to decide on the data frequency (i.e. daily, weekly or monthly returns), which will influence your calculations of risk (i.e. standard deviation or another measure such as CAPM beta). You should then proceed to use performance measurement techniques discussed in ASB3215.

You will need to decide on the number of assets in the portfolio and to identify an appropriate benchmark of past performance. In ASB3215, we will discuss benchmarks and some methods of performance measurement. Of course, you should refer to textbook(s) and there is a vast amount of online resources on these aspects.

On the previous page, the briefing refers to European markets. This is partly because you have access (via Bangor University library) to the online databases named Amadeus and Orbis BankFocus which can potentially provide suitable data. However, if you prefer to study non-European markets for this assignment, that is permitted but you will need to collect the data from different sources e.g. free online databases. If you take the latter approach, you must explain this in detail within your report.

The data period must be 2011-2020 (you must include 2020 due to the global financial market turbulence of last year). Your Excel file will be part of the submission hence the raw data, the data preparation and the calculations are part of the assessment.

This assignment provides an opportunity to engage with real-world issues in portfolio management and to apply concepts from this module and possibly from other modules that you have completed. It enables you to improve your skills in data collection, data analysis and Excel. Guidance is available from the module leader, but you must engage in the work from an early stage in the semester. The module leader might be on Easter leave between 29th March and 9th April, so you should bear that in mind in your planning. The Easter period should be primarily used for final polishing of the work.

The assignment will be assessed on the following criteria:

Ability to devise a plausible equity investment strategy;

Ability to collect real-world data and to implement analysis in Excel;

Quality of the interpretation of your research;

Ability to convey your analysis in a concise and well-presented report, including tables and graphs.

Use 12-point font and 1.5 line spacing. Ensure full acknowledgement of your sources of information and data. Your reference list should include at least five academic journal articles. If desired, an appendix can be used to present the most technical details. The word count (excluding the reference list and appendix) must be stated on the cover page.

Electronic submission only. The document and Excel file will be submitted via separate links within the Blackboard module. If you work in a group of two: only ONE copy of each file (Word and Excel) is to be uploaded. Both names and student numbers should be stated on the cover page.

The assignment accounts for 50% of the module assessment, with the remaining 50% weighting on the May exam.

Additional advice

1. Here are some key elements in the approach to the assignment.

(i) choosing an investment strategy i.e. a basis on which to select which assets will be in your portfolio. You can think of it this way: there are thousands of stocks/funds available for an investor to choose, so your task is to define criteria with which to choose a subset of stocks/funds. To make the assignment work realistic (in terms of your time and effort), I am suggesting that you choose a small number of assets. This means that you will not necessarily have a well diversified portfolio, but that is not part of this particular assessment task. To incorporate the diversification concept, you could choose a set of funds (e.g. mutual funds or ETFs) rather than a set of stocks.

(ii) being able to provide a rationale for the choice of investment strategy.

(iii) deciding on which assets will enter your portfolio (I recommend between 5 and 10 assets; a fund counts as one asset).

(iv) engage in an academic literature review (you will need at least five articles to be cited in your final assignment document).

(v) consider what data sources you will use.

(vi) calculate returns (use the information from ASB2217 / 3217). Start with the stock returns then combine them to calculate your portfolio return. ASB2217/3217 refers to expected returns but here you are using past data hence they are actual returns (essentially the same formulae).

It is preferable to use logarithmic returns at the monthly (or weekly or daily) level. When you take averages across multiple time periods, it is more technically correct to be using the log return rather than the arithmetic return.

(vii) use methods covered in the ‘Performance Measurement’ lecture topic to consider your portfolio’s performance. You will need to choose a benchmark index and collect data for this benchmark and for a risk-free rate (e.g. Treasury bill or bank base rate).

Start with the simplest approach, which is the Sharpe ratio. You can also consider using the information ratio. The main calculation is for the sample period as a whole. However, your analysis can be extended by also calculating the ratios separately for each of the ten years in your sample. Also, potentially for the first half and second half of the sample period. An extension would be to isolate the impact of 2020 on your results.

(viii) To extend the work and to be more ambitious:

You then proceed to calculate other measures, for example the Treynor ratio and the Jensen measure. For the portfolio beta, you can utilise the covariance function in Excel. To calculate measures for the benchmark, you have two possibilities: (i) assume that your benchmark portfolio is ‘the market’ hence it has a beta of one; (ii) have two data series i.e. your chosen benchmark plus a broader market index. In the latter case, you will have a benchmark with a beta not equal to one.

(ix) Further ambition can be reflected in additional comparisons and reflections based on academic journal articles.

2. The risk-free rate

For calculating the excess portfolio returns and excess benchmark returns, you need to collect the risk-free rate data. This can be the central bank base rate or the Treasury bill rate. Central bank websites are typically the easiest source to use.

For the UK, here is the bank base rate data:

https://www.bankofengland.co.uk/boeapps/database/Bank-Rate.asp

Crucially, this is annual data. You will need to adjust these annual rates of return to a different frequency, i.e. most of you will be using monthly or daily frequency for your portfolio and benchmark returns.

For the last 10 years, many developed countries’ base rates have been very low (e.g. for the UK, at the time of writing this document it is 0.1%, the lowest ever rate). Therefore, when you convert the annual rate to monthly, it will be a very small value (and if you convert to daily, it will be miniscule).

If you are using Treasury bills, the 3-month rate or 1-month rate are the most appropriate. One possible source: https://www.treasury.gov/resource-center/data-chart-center/interest-rates/Pages/TextView.aspx?data=billrates

You need to download the time series i.e. you should be using a different rate for each year in your sample period. Remember to adjust annual rates to the frequency of your data e.g. monthly.

Also, if a particular observation of the risk-free rate is quoted as (e.g.) 1.5%, you need to convert this to 0.015 before adjusting it to the frequency of your data

e.g. a simple conversion would be 0.015 / 12 (for monthly data).