Part 2: Portfolio Optimization Software

GSM Capital, a large investment bank, is attempting to market its new asset allocation product that provides its clients with personalized advice. The slick Excel-based product, dubbed "UCD GSM Portfolio Optimizer" provides asset allocation mixes over 5 asset classes and one risk-free asset. Investors can use the product in two ways. They can either input their risk aversion, or they can specify a target expected return for the portfolio.

The portfolio optimizer can be found on the class website ('GSM Portfolio Optimizer.xlsx'). The firm's current Capital Market Assumptions for asset classes have already been entered for you. A Technical Appendix (below) provides more detail on its function.

To make sure the product is indeed robust and yields sensible results the Vice-President in charge of this project has tasked you to test the product. You are asked to see if the recommended portfolio produced by the software makes sense. He has the following questions:

Questions

a) Measure what the benefit of diversification is for someone who is 100% invested in the U.S. What is the increase in the expected return that can be achieved for the same level of risk? (Hint: use 'Goal Seek' or 'Solver').

b) What is the highest expected return you can obtain if you accept 20% volatility of risk? What is your allocation in the risk-free asset?

c) Can this optimizer recommend a portfolio that provides the highest expected return with a risk of 20% volatility, but without borrowing cash?

d) At the expected return you use in (a), a very small amount of wealth is allocated to Emerging Markets (EM). The VP in charge of this project asks, "Is there something wrong with the inputs?". Try varying various inputs to get the allocation to EM up to 20% of the Mean-Variance Efficient (MVE) portfolio (without cash). Try varying

the expected return of Emerging Markets

its volatility of Emerging Markets

the Emerging Markets-US equity correlation.

In each case, describe your experience. How does the allocation to EM change when you change these input variables? What is the intuition behind these effects?

e) Among the capital market assumptions in part d), which parameter is your results most sensitive to if we want to increase allocations to Emerging Markets? That is, if you vary a parameter by 0.01 (or 1.00%), which parameter makes the largest difference?