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Built to Suit
Customized Portfolios
In wealth management, customization is motivated by a set of real-life conditions (need) or a desire for a certain performance (choice).
Choice or Need
To take this from conceptual to actual, let's think about two very different (and very simplified) scenarios.
​​SCENARIO 1:
An individual aged 29, with a retirement income goal of 'X'. This individual has 'Y' amount of assets, 'Z' amount of savings per year, and about 35 years until retirement. In this scenario, if any of the previous (assets, savings, time) don't allow for the individual to accomplish their goal then customization is determined by necessity.
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SCENARIO 2:
An individual aged 67, already retired, and living comfortably on retirement savings that provide the correct amount of retirement income to support their lifestyle. In this scenario, none of the inputs from Scenario 1 (assets, savings, time) interfere with the individual's goal which allows the individual the freedom to approach their customization not by necessity but by their preference, or choice.
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Between scenarios 1 and 2, there are an infinite number of combinations for which customization can be done. All of them are determined by need and choice.
Need-Based
Customization
Scenario 1
The individual in Scenario 1 has a set of inputs that drive the need for customization. Those inputs (again, very simplified) are their assets, savings, and time. As we described before, any of those inputs can prevent the individual from achieving their goal. Let's say that the input in question is assets - the value of their assets currently is too little to allow for the goal to be accomplished in the future. As an example of this, if the individual has only $10 in assets this year, even with a guaranteed annualized return of 20% they will retire with only about $7,100.
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This is where it becomes obvious that customization will be determined by need and not by choice - $7,100 is most likely not enough to retire on.
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Assuming all of the inputs remain the same, the deficit relative to the individual's goal will necessitate (with the approval of the individual) the customization of the portfolio to an allocation that will increase the chance of achieving the goal.
Choice-Based
Customization
Scenario 2
In Scenario 1, the reason for selecting one convex portfolio allocation over another was that if that selection was not made the chance of achieving the goal was significantly reduced. In Scenario 2, the reason for selecting the convex portfolio allocation is entirely different.
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In the absence of necessity, the portfolio owner can make a selection based on their preference, or choice. There may be no reason whatsoever for the selection other than it is what the portfolio owner prefers. In this case, the portfolio owner has total control over customization because the customization is based only on their preference.
How do we customize on a need basis?
How would one construct a portfolio with a given set of conditions unique to an individual investor that accommodates those conditions and uses convex execution?
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The motivation for this type of portfolio construction is to pair the performance of a convex portfolio with the unique conditions of the investor and the investor's goal.
The way that this is accomplished is through the adjustment of the convex portfolio to fit the requirements of the investor. We can examine the method of adjustment using a concept from finance called the Efficient Frontier.
Return & Risk
Optimality
Optimality can be found in many areas including investing, engineering, economics, biology, and art.
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For example, it is thought that the composition of Leonardo da Vinci’s famous work, "The Mona Lisa" is optimal; where Mona Lisa's face is relative to her hands, where her mouth is relative to her eyes, and so on.
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The location selection of all the component pieces causes the optimality of composition.
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In this same sense, portfolio construction is an art as well. How the portfolio manager determines the individual investments of the portfolio in relation to each other to accomplish the goal of the portfolio is similar in concept to how da Vinci determined the composition of the subject to accomplish the goal of the artwork.
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Regardless of whether the artist is creating a painting or a portfolio, there is an optimal way by which to do this recognized in the end result of either; one result is value in the form of beauty and art, and the other is economic value.
For da Vinci, the proof of optimality is how the painting is deeply pleasing to the viewer's eye. For the portfolio manager, the proof of optimality is if the performance of the portfolio is pleasing and accomplishes its goal. This is measurable and expressed as a positive (negative) number. However, measuring optimality in investing is more science than art.
Let's review how this is done.​​
The Efficient Frontier
The Efficient Frontier is a graphical representation of the relationship between return and risk.
In the graph, return is on the y-axis, risk is on the x-axis, and the line on the graph represents every portfolio that is generating the highest expected return for the specific level of risk it is taking; the Efficient Frontier.
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The portfolio that has the optimal combination of return and risk is at the point on the line where return begins to increase less than risk increases. If one were interested in a portfolio with the optimal combination of return and risk, one would select this portfolio.
Let’s call this the ‘Optimal Portfolio’.
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The Optimal Portfolio
The performance of the Optimal Portfolio is generally what we aim for when creating convex portfolios for our clients. Once you go beyond this point, risk is increasing faster than return is increasing. This means the relationship between return and risk is going from optimal to less than optimal.
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But, as we noted before, many people require a customized portfolio specific to their needs. This is the necessity-based customization scenario, or Scenario 1 described above. In this case, an investor may not need to take as much risk as the Optimal Portfolio. So, they can have a portfolio that is a bit further down the Efficient Frontier; it takes a little less risk and may generate a little less return as a result. This is the 'Low-Risk Portfolio'.
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The opposite can be true as well, and a client may need a portfolio with a higher amount of return which would come at the cost of a greater amount of risk. In this case, the investor can have a portfolio that is a bit further up the Efficient Frontier; it takes a little more risk and may generate a little more return as a result. This is the 'High-Risk Portfolio'.
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Having the ability to build a portfolio at multiple points on the Efficient Frontier allows us to provide customized convex portfolios for our clients.
This is done for clients on a necessity basis, a choice basis, or a combination of the two. What determines this just depends on whether the conditions of the client’s life demand it (necessity) and/or allow it (choice).
