Clients may hold multiple assets in their portfolio, but is their asset allocation optimal? Creating the most optimal portfolio for clients, building relationships, understanding their investment goals and risk appetite and generating new business are some of the major responsibilities that financial advisers juggle with. In an evolving investment landscape, attracting and retaining clients requires advisers to continuously prove the value of their services. But given the multitude of responsibilities, advisers are often faced with a dilemma: how can they enhance their clients overall experience?
Research suggests that the solution could lie in outsourcing asset allocation to an expert. Advisers can focus more on building relationships with clients’ and leave asset allocation to the expert. Keeping this in mind, we have launched the Morningstar Model Portfolios which are designed to give you access to the experience and expertise of the Morningstar group. Our model portfolio solutions can help advisers enhance investment offerings, strengthen client relationships and streamline business.
Morningstar offers model portfolios ranging from cash plus to adventurous which are built for the long term, with a keen eye on risk and created to help meet your clients’ needs at each stage of their life. Constructing a model portfolio for clients involves a series of steps. Within each step, we apply various models and concepts that have been extensively researched and tested through practical implementation over a period of time.
Empirical studies show that asset allocation is one of the most important factors in determining portfolio performance. It puts the principle of diversification to work so that when some asset classes are experiencing a downturn, others may be experiencing stronger performance. However, asset allocation does not eliminate the risk of experiencing investment losses.
The traditional approach to asset allocation
Our first communication on Are your clients’ portfolios optimal? gave insight about Morningstar’s capital market assumptions, or CMAs, and the drawbacks of using naïve processes for deriving estimates that are used in mean-variance analysis.
Advisers use various methods in determining the asset allocation mix for a client, of which, two popular methods are mean (expected return) variance (or standard deviation) optimization (MVO) and age rule of thumb. Mean-variance optimization provides a mathematical framework for generating portfolios that maximize expected return for a given level of risk and minimize risk for a given level of return (optimal portfolios). Age rule of thumb is simply 100 minus client’s age. Under this rule, you advise 100 minus your client’s age in stocks. For example, if your client is 40 years old, you would advise clients to invest about 60% in stocks. Taking a traditional approach by just using these two techniques will lead to a less diversified and sub-optimal portfolio.
There are several drawbacks of using a traditional approach.
First, age rule of thumb ignores critical variables such as risk tolerance and the time horizon.
Second, traditional mean-variance approach assumes asset class returns are normally distributed i.e. returns lie between plus-minus three standard deviations; which in reality is not the case (for example 2008 for equities and 2013 for fixed income).
Third, it does not account for uncertainty in the capital market assumptions (or asset class risk & return estimates) due to which resulted asset mixes can be very sensitive to small changes in assumptions.
Fourth, the asset allocation is less diversified and sub-optimal as it ignores downside risk.
Morningstar’s way of asset allocation
When creating portfolios at the asset class level, Morningstar focuses on three major qualifications: (1) efficiency and robustness, (2) investor preferences, and (3) investability. We employ multiple techniques while developing strategic asset allocation models. Given that traditional approaches have their limitations, we try and overcome these by using techniques such as re-sampled mean variance optimization and mean conditional value-at-risk (M-CVaR).
Risk and return estimates are not known with certainty; therefore, it is necessary to account for the uncertainty in these estimates. This uncertainty can be accounted for by using re-sampled MVO. The resampling technique is a combination of Monte Carlo simulation (which helps in generating multiple forecasts for the capital market assumptions) and traditional MVO. Also, there is considerable evidence that clients’ preferences go beyond mean and variance. Clients are particularly concerned with significant losses, i.e. downside risk. One of the promising alternatives to the traditional MVO technique which focuses on the downside risk is called mean-conditional value-at-risk optimization (M-CVaR). CVaR measures the expected loss of each asset class which more accurately captures the downside risk and its impact on the overall portfolio. For example, if the 5% CVaR of a portfolio is 30%, it means that average loss of worst 5% outcomes is 30%. The result of using a combination of these techniques is an optimal asset mix for each risk profile based on practicality and investor preferences.
Morningstar’s asset allocation models are governed by the firm’s Global Asset Allocation Sub-Committee. This committee, which is part of the investment management group’s Global Investment Policy Committee structure, is comprised of senior investment professionals across our investment teams in Australia and Asia.
Since asset allocation forms the base of a model portfolio, it is important that these asset mixes are backed by sound research and are not just based on a traditional approach. Morningstar’s asset allocation models are then clubbed with mutual funds to construct model portfolios.
About Morningstar model portfolios
Morningstar Model Portfolios are based on more than 30 years of groundbreaking research on long-term strategic asset allocation. Our goal is to provide exposure to a broad range of asset classes that can be weighted according to our expectations of risk and reward.
In investing, the basics matter. That's why we begin with our own research showing that the mix of assets in a portfolio can have a greater impact on investment returns than timing markets. Guided by this research, we use risk and return forecasts across domestic asset classes and international equities to develop a strategic asset allocation for each portfolio. Independent and Institutional advisers can use these portfolios to help clients reach their financial goals.
We’re committed to helping independent and institutional advisors create better outcomes for their clients. You know your clients’ needs and how to build plans to meet them. We combine our investment knowledge with portfolio construction experience to provide investing solutions that put your clients first.
In our next series of communication, we will give more insight on how you and your clients can benefit from Morningstar’s Model Portfolios – Stay Tuned!
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