Research Project

Assignment:

Write a research report in response to an RFP(request for proposal) for an equity/cash asset allocation for a major university endowment of $10 million.

The committee has decided to only invest in the market and 2 industry portfolios and risk free assets. You will need to analyze the 5 industry portfolios and choose the best two to include in your portfolio for consideration

All respondents have been asked to utilize data available in the Data Library of the free website:

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html

for these asset classes. The recommended monthly data sets are:

Fama/French Factors (for the market return)

5 Industry Portfolios (for 2 portfolios)

Your analysis must be professionally written and with a diversified audience in mind. While all investment committee members are investment professionals, not all are ‘research-quantitative’; some are portfolio managers, some analysts, and some regulatory compliance experts. In addition, once your report is discussed and approved by the committee, its recommendations will be reviewed by the full Board which contains a broader mix of professional backgrounds.

Report Specifications

The RFP requires that all reports are structured in the same way to facilitate committee review, evaluation and comparison. There is a maximum report length specification of 8 pages, including all attachments, set in Times New Roman, 12 pt minimum type font.

Create Excel sheets to show work. However, the report must be self-contained and not require the committee to seek out needed information in the spreadsheets.

The report is to include sections which address the following:

Data discussion: identify time period used of data set, the committee has requested that historical data prior to 2010 not be used in calculating expected returns, variances or covariances. Discuss your reasoning for selecting the indexes you use.

Summary return data analysis of the Fama/French factors and the market portfolio: means, variances, standard deviations, covariances, correlations, etc.

Equity Efficient Frontier: Develop a graph of the frontier from minimum to maximum monthly returns possible using the 3 equity series, assuming no shorting (i.e., negative allocations). Develop a table showing the allocations associated with returns of: 0th, 20th, 40th, 60th, 80th and 100th return percentiles.

Identify the asset allocation that maximizes the committee’s utility, using:

U = E[r] – . 5AVar[r]

with E[r] and Var[r] defined in appropriate units. Perform this evaluation once for the committee’s conservative members (A=4.0) as well as its aggressive members (A=1.0).

Based on an assumed risk free rate of 2.0% on an annual basis, find the optimal risky portfolio (ORP) on your efficient frontier, and identify its asset allocation.

Using the above utility functions, find the utility maximizing allocations between the ORP and T-Bills, with and without shorting, and display the implied allocations to the different asset classes.

Make a firm recommendation on how the committee ought to allocate its assets: all equity or equity plus T-Bills, and defend it based on your analysis. If necessary, make one firm recommendation for each of A=4.0 and A=1.0.

Thoughts/Comments/Hints:

Begin this project with a review of the above website. Understand what data is there, how Kenneth French developed it, and why the cited data sets are most appropriate for this analysis

If you are finding market returns do not just use Mkt-rf, add rf to Mkt-rf to isolate the markets return. Explain where your data comes from.

Data can be messy, and you need to address at least the following issues:

Annual, monthly or daily data are available. Assuming that the committee intends to rebalance to the portfolio allocation targets at its monthly meetings, are you comfortable with the recommended data?

Use Value-weighted returns.

Please note: the units of the data, make sure to compare like to like. The data are percentage returns written as 8 instead of .08, it is recommended to convert all returns to decimals before any analysis takes place. Remember to do all comparisons in annual returns, know how to convert monthly to annual returns and variances.

You need to develop the efficient frontier. Before you begin, think about the range of returns you expect on this frontier. The range of Variances or SDs can’t be done in your head, but the returns can (why?).

Simulation: In Excel, randomly generate allocations. Here’s an easy way: generate 3 random numbers between 0 and 1, using Rand(), call them R1, R2, and R3. Use: R1/(R1+R2+R3), R2/(R1+R2+R3), R3/(R1+R2+R3) as the three weights. Plug each allocation into the Expected return and SD formulas and save output (as it will keep changing). Annual expected returns can be rounded to the 4th decimal place. Repeat 1000 (or 5000) times. Sort the data by increasing return, and within that by decreasing SD. The efficient frontier is the set of points that gives you the lowest SD for each return. Experiment with different numbers of simulations. With this approach, you get the added benefit of developing a scatter diagram of feasible portfolios in risk-return space. Just plot all the (SD,R) combinations.

Type of service: Academic paper writing

Type of assignment: Project

Subject: Finance

Pages/words: 8/2200

Number of sources: 6

Academic level: Undergraduate

Paper format: MLA

Line spacing: Double

Language style: US English