Designing a successfully absolute return investment solution is not as easy as it may seem. Very often the investor’s needs are not adequately understood and the proposed solutions fail to meet the promises made. By following the proposed eight steps, you will significantly increase the chances that your future absolute return solutions will regain the investor’s trust.
Absolute return investment solutions, also known under the names of total return or target return solutions, have seen bad lights over the recent years. In many cases this is due to failing to meet the promises made., partially because of poor expectation management or otherwise said, poor understanding of the investor’s needs. But it was also often a consequence of the unavailability of adequate skills to meet the promises made.
By following these eight steps, you will significantly increase the probability that your future absolute return solutions will regain the investor’s trust.
Step 1 – Understand the investor’s needs
The first step in designing an absolute return solution is to understand the investor’s needs. What does the investor want to achieve? It is important to distinguish between wants and needs. An investor’s may want to achieve 4% return per year but his need is to match the interest payments on his mortgage.
Determining the investor’s needs also requires understanding the balance between return expectations and risks.
- Some investors want to achieve a decent return under the conditions that no money is lost.
- Others tend to focus on return maximization, accepting from time to time small losses.
- Again other investors aim at maximizing the probability of satisfying their needs, without aiming at exceeding them.
Step 2 – Determine the investor’s risk profile
Especially with respect to absolute return solutions, investor’s exhibit different risk profiles. For some, absolute return means, no loss whatsoever. Others want to avoid frequent losses or large losses. And even others define risk as strong correlation with equity markets or interest rates.
Risk profiling should capture the three dimensions:
- risk capacity, the objective amount of risk the investor is capable of accepting,
- risk tolerance, the subjective perception of risk that allows the investor to still “sleep well”, and
- risk requirements, the minimal level of risk needed to be taken in order to satisfy the investor’s needs.
Step 3 – Identify the investor’s investment horizon
Although very often not explicitly formulated, most investor’s needs have an associated time horizon. This may be financing college for his children, buying that eagerly anticipated Ferrari at retirement, or just being able to afford that Christmas present. Therefore, objectively, absolute return solutions would only be required to satisfy the investor’s needs at maturity.
But more often than not, the investment horizon includes and emotional component. For example, the investor assesses his wealth at the end of each month, quarter, year, and wants his expectations met at that time. Others again expect from an absolute return solution positive return at any given moment in time.
Step 4 – Assess the feasibility of the investor’s expectations
Very often investors want to have the egg and the chicken, which is not possible. Therefore, before stating the design of the absolute return solution, the feasibility of satisfying the investor’s needs should be reviewed. This means answering the question: Is it possible that somebody could achieve the targets derived from the investor’s needs, risk profile, and investor horizon?
Step 5 – Identify your skill set
After having assessed the feasibility you should identify the skill set available. What are you good at? Do you have financial engineering skills? Is your expertise in econometric modeling? Or are you gifted in analyzing complex causal relationships in real-time? Only real skills will allow to turn somebody could achieve the targets into you could achieve the targets.
Step 6 – Define the investment approach
There exist three types of approaches to produce absolute return solutions. They distinguish themselves in the needs satisfied and more importantly in the skill set require producing them. You should choose the one that best matches your skill set without losing sight of the investor’s needs.
In an algorithmic approach, a one-time defined algorithm describes how the investment portfolio is to be managed over time. For example, the CPPI (Constant Proportion Portfolio Insurance) algorithm, guaranteeing no loss at maturity, falls into this category. Algorithmic approaches allow designing solutions that guarantee their result.
Statistical approaches assume that given statistical properties hold. These properties are generally based on econometric or economic models. One such model could be that there exists an equilibrium price that any stock will achieve eventually. Under the assumption that the statistical characteristic holds, absolute return targets can be achieved.
Forecasting based approaches
In contrast with algorithmic and statistical frameworks are forecasting based approaches build on market expectations developed over the lifetime of the absolute return solution. These forecasts, which may be of quantitative or qualitative nature, are in real-time translated into investment portfolio positions. With a majority of correct forecasts absolute return targets can be achieved.
Step 7 – Develop an investment process
Developing an investment process means defining how the absolute return solutions will be managed. A generic investment process is comprised of the following steps:
- Collect and generate market data and, depending on the approach, formulate forecasts.
- Construct an investment portfolio based on step one.
- Structure the constructed investment portfolio so that it satisfies the investor’s risk profile.
- Derive transactions based on the structured portfolio in step three and execute them in the open market.
- Review and monitor the results achieved.
Step 8 – Test the developed solution
Before actually launching the newly developed absolute return solution, you should thoroughly test it. If you based your solution on quantitative models, have them reviewed and validated by an independent expert. Test your approach not only under normal market conditions but also apply scenario and extreme event analysis. Are the results in-line with the investor’s risk profile?
Review the results from the tests and adjust you investment process accordingly. Eventually improve your skill set.
Once all eight steps have successfully been completed, you can start digging in the dirt, that is, launch your new solution. And always remember, the result will be only as good as the combination of its design and you skill set.