This section should outline the aims of the analysis, briefly identify the data and methodologies to be used, and set out the structure of the remaining sections of the report.
2. BACKGROUND TO THE DATA SAMPLE (20% WEIGHT)
In this section, you should identify the companies in your portfolio and give any information which may be relevant to your analysis (for example, the industries the firms operate in and their relative size).
You need to identify the portfolio you are interested in (i.e. the Weights which are initially invested in each company). These should be the weights you identified for the Optimal Portfolio (No Short Selling) in the Portfolio Analysis computer lab session.
You will need to provide a table of summary statistics for each of your shares individually and for the portfolio (this will require you to calculate portfolio values and hence returns for each day in the 10 year data sample). Comment on the main features.
Include a histogram of the empirical returns to each share and to the portfolio, overlaid with the normal distribution with the same mean and standard deviation of returns (you saw how to do this in the Returns in Finance computer lab session). Comment on the normality / non-normality of the returns.
(NOTE: formal tests of normality are not required as we have not covered these in ASB4416, but you are welcome to include them if you wish to do so)
3. ANALYTIC VAR (10% WEIGHT)
This section should describe your calculation of the 260-day analytic VAR for your portfolio of 4 shares, using 95% and 99% confidence levels.
Choose a sensible initial portfolio value to use throughout your analysis. Make sure you include a discussion of the advantages and limitations of this approach as it applies to your data.
4. MONTE CARLO VAR (15% WEIGHT)
This section should describe your calculation of the 260-day Monte Carlo VAR for your portfolio of 4 shares, using 95% and 99% confidence levels.
You need to include details of the main steps, but these should be brief and to the point (this is NOT an essay on Monte Carlo methods, but the reader will need to know how many simulated paths you used, etc). Again, include a discussion of the advantages and limitations of this approach as it applies to your data.
5. HISTORICAL ANALYSIS / BOOTSTRAP VAR (15% WEIGHT)
This section should describe your calculation of the 130-day and 260-day Bootstrap VAR for your portfolio of 4 shares, using 95% and 99% confidence levels. Again, you need to include details of the main steps, but these should be succinct. Include a discussion of the advantages and limitations of this approach as it applies to your data.
6. DISCUSSION (25% WEIGHT)
This section should clearly demonstrate your understanding of the calculations you have performed in the previous sections. you need to compare and contrast the results you obtained, explaining clearly (with reference to your data section) which features of your data set may be driving particular results.
How similar are the results from the three methods? For some of you they may be comparable; others will find a much higher degree of dispersion.
Either way, discuss the reasons why the different methods give the degree of dispersion you obtained.
Finally, you should refer back to the advantages and limitations of the various approaches as applied to your data (identified in Sections 3-5) to provide a balanced view of which approach you would place most confidence in as an investor. To what extent is your conclusion likely to be robust in all portfolios and to what extent is it diven by the articular features of your data sample?
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