While you are investing your capital of $1 million in your Interactive Brokers account according to your investment mandate, you are asked to develop a portfolio strategy, that is, come up with broad asset class return assumptions upon which you can develop a hypothetical plan (no trading) to allocate capital efficiently among risky asset classes and a risk-free asset so you achieve the lowest volatility for a given level of expected return.

While you are investing your capital of $1 million in your Interactive Brokers account according to your investment mandate, you are asked to develop a portfolio strategy, that is, come up with broad asset class return assumptions upon which you can develop a hypothetical plan (no trading) to allocate capital efficiently among risky asset classes and a risk-free asset so you achieve the lowest volatility for a given level of expected return.

You may allocate capital efficiently using Markowitz’s mean-variance framework based on the lecture and in-class discussion on Chapter 7: Optimal Risky Portfolios of the Bodie Kane Marcus (BKM) textbook.

I recommend you use broad asset-class ETFs for your portfolio allocations: global stocks, global bonds, and cash in USD (since you are US-based investors). Use ACWI for global equities, BNDW for global fixed income, and GBIL for 0-1 year Treasuries, which will be your proxy for USD cash.

You may allocate it in any proportions you deem prudent. For example, 60% equities, 35% fixed income, and 5% cash is a typical allocation in portfolios of investors with a moderate risk tolerance. However, my preference will be for you to allocate it in a mean-variance efficient manner.

The attached Excel workbook has the Solver Add-in. It is described in Appendix A of BKM Chapter 7, pp. 230-234 (or pp. 232-236 if you have the 11th edition). In the attached version, I have modified it to solve only for three assets: ACWI, BNDW and GBIL, and left Assets 4 -7 as placeholders for potential future use when more assets may be in your investable universe.
I have downloaded historical price data from to calculate daily returns, return standard deviation, variance and covariance for ACWI, BNDW, and GBIL, in the corresponding tabs added to the workbook. I have calculated annualized standard deviations, variances and covariances using 252 trading days per year.

My expected annual return assumptions for the three asset classes are: 8.5% for global equities, 2.5% for global fixed income, and 1% for USD cash. They are entered as inputs in cells B5:B7 of the main spreadsheet, and the rationale for each of them is shown in cells C5:C7.

As part of this portfolio strategy exercise, I expect you to come up as a team with your own return assumptions for the three asset classes and provide a sound rationale why you have made these return assumptions.

Using your expected return assumptions and the volatility, variances and covariances from the historical data, create the efficient frontier using the Solver as described during class and in the BKM textbook: find the minimum-variance portfolio, the maximum-Sharpe (or tangency) portfolio, and other portfolios along the efficient frontier by gradually increasing your required portfolio return. As I do in the spreadsheet, you may use GBIL as one of the risky assets that go on the efficient frontier, and not as the risk-free asset on the y-axis, as in the strict theoretical sense.

Do not have short positions (i.e., negative weights) in any of your assets. The optimizer will provide solutions with positive weights only if you check the box “Make unconstrained variables non-negative” in the dialog, as I do.

After you have built the efficient frontier, you may pick a point on it and implement it as your Investopedia portfolio. The optimal (maximum-Sharpe or tangency) portfolio is typically used. In my frontier, optimized using my return assumptions, it came out as the outermost point with a 100% allocation to ACWI, 0% to BNDW, and 0% to GBIL. When you use your return assumptions, the tangency portfolio will most likely be different.
Provide a short write-up discussing your return assumptions, your optimized efficient frontier (provide the main tab of your spreadsheet) and the recommended portfolio from it.

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