Asset Allocation Modeling for Foundations and Endowments
While most investment consultants agree that asset allocation policy is the primary determinant of portfolio return, the implementation of this concept varies widely in practice. Asset allocation policy requires an investor to answer several key questions:
- What is my investment objective?
- What is my time horizon?
- What is my tolerance for risk?
- What are my spending/payout needs?
- How many and which asset classes should be included in my portfolio?
- What percentage of my portfolio should be allocated to each asset class?
Investment Objectives, Time Horizon, Risk Tolerance, and Spending
When working with new clients, some investments consultants will discuss three broad investment objectives: stability of principal, spending, and growth. Investment consultants may also discuss three broad time horizons: short-term (one to three years), medium-term (three to five years), and long-term (five years or more). In addition, the client’s tolerance for risk and spending/payout needs will be discussed. Often, there is a disconnect between the client’s investment objective and their tolerance for risk or between their time horizon and their spending needs. For example, a client may not only define their objective to be growth but also their tolerance for risk to be low. For a client who wants to grow their portfolio, they must be willing to take on a higher level of risk. The investment consultant’s role is to help each client understand the relationships among their investment objectives, time horizons, risk tolerance, and their spending needs.
Asset Allocation Policy—Managing Risk and Return Expectations
Asset allocation policy defines the number of asset classes in a portfolio and the percentage allocation to each asset class. How can the concept of asset allocation be applied to the question of balancing risk and return? Do risk and return really move in lockstep or are there ways in which higher expected returns can be achieved without taking on more risk? The goal is to achieve an appropriate level of expected return for the corresponding level of expected risk. Graph 1 below illustrates a base case hypothetical asset allocation model with three asset classes. In this base case scenario, point A represents domestic bonds, point B represents domestic large cap stocks, and point C represents domestic small cap stocks. The investment consultant’s task is to determine the appropriate percentage to allocate to each asset class.
The points are plotted based upon their historical return and risk characteristics. In this example these are hypothetical. The essence of asset allocation modeling is to combine a set of asset classes that are not highly correlated. Highly correlated asset classes would move in the same direction at the same time and with the same magnitude.
The green line that connects points A and C is known as the efficient frontier. Simply, the efficient frontier represents the most efficient combinations of these three base asset classes. In this example, there are no combinations of these asset classes that would provide more return with the same amount of risk or less risk with the same amount of return. If an investor prefers a low-risk portfolio, then a point on the left side of the curve would be appropriate. However, a low-risk portfolio is not expected to produce high returns. In the base case scenario, point 1 illustrates the historical risk and return of a hypothetical portfolio that would include the base case asset classes. In this example risk is defined as standard deviation.
Is there a way to increase the historical return of the portfolio without an increase in the historical risk? What happens if we add an asset class to our base case portfolio? In graph 2, domestic real estate (point D) is added to the portfolio. This hypothetical domestic real estate asset class has not only produced higher returns historically but has also been more volatile than the other hypothetical asset classes. The addition of domestic real estate to the portfolio creates a second efficient frontier line in blue. With domestic real estate in the portfolio, the efficient frontier moved up! Now the portfolio (point 2) would have a higher historical return with the same level of historical risk.
Investment consultants utilize portfolio modeling software to conduct efficient frontier analysis with actual historical risk and return data. Efficient frontier analysis is just one of the powerful tools used by investment consultants to form their asset allocation recommendations.
Will Thorpe is the Chief Marketing and Development Officer for Mason’s institutional practice. For more information about Mason’s asset allocation research or more information about Mason in general, please send an email to email@example.com or visit masoncompanies.com/services/institutions.
Mason Investment Advisory Services (Mason) was founded in 1982 and today they manage investments for private clients and institutions nationwide. Mason works with 18 nonprofit organizations in Indiana, 16 of which are community foundations. The company was hired by its first nonprofit client in 1998 and their first in Indiana in 2006. Today, Mason works with over 80 institutional clients nationally and manages over $4.4 billion in assets for these clients and over $8 billion as a firm.
In their last IPA blog, Mason addressed tactical versus strategic investment approaches. In this blog, they discuss asset allocation modeling and one of the tools used to construct allocation plans for foundations and endowments.