Complicated tasks are often described as requiring a mix of artistic and scientific sensibility.
That is certainly true for the process of selecting an investment manager for inclusion in a client’s portfolio. A broad set of characteristics must be evaluated relating to the organization, investment strategy, investment process and legal terms, with the ultimate goal of truly understanding the prospective risk and reward potential. At Silvercrest, we have separate teams dedicated to evaluating these attributes from both an investment and operational perspective. The vast experience of our team allows us to weigh the various attributes and make thoughtful decisions on some of the more “artsy” topics such as minimum length of track record, ideal assets under management, centralized vs. consensus decision making or even questions such as whether we prefer a manager that has learned from a big mistake or one that has yet to confront that type of challenge. Some of these decisions can be informed by applying the “science” of quantitatively studying the empirical evidence, and our team is constantly looking for ways to quantitatively answer what are—on the surface—seemingly more qualitative types of questions. We have built robust manager performance evaluation reports, portfolio management analyses and risk models that allow us to quickly evaluate managers from a quantitative perspective, but there is also an art to using the science.
One example of the art of using the science is demonstrated by the process of selecting one manager from a list of potential candidates to include in a portfolio. Many investors focus on either an interesting narrative or strong results relative to peers, often ending up either chasing returns that fade or owning a collection of what could be called “fads.” Other investors focus on mean reversion or value, which is problematic if there is no particular catalyst for a reversal. At Silvercrest, our approach begins with asset allocation, which completely changes the approach to selecting a manager. Asset allocation determines which types of managers we need, and then we seek the one that best fulfills that specific condition. If we are looking for a small-cap value manager and we find one that has dramatically out-performed the peer group, with 1,500 bps of alpha over the prior year, that will initiate more skepticism than interest. Our analyses and reporting will then allow us to determine whether the outperformance came from strong stock selection, for example, or a bet on a different asset class outside of the specific exposure that we are looking for. A good analogy can be made to the process of buying a car. If we require a sport utility vehicle that can handle our winter trips to the ski house, high up in the snowy mountains, and the salesperson shows us a beautiful sports car, we may reason that most of the time, we aren’t in the mountains, and we may become tempted to take the offer. After buying the sports car, it may fulfill our needs for some time but when we try and drive it up the mountain, there is a good chance we are going to end up in a precarious situation. This is not to say that there isn’t room in the portfolio for a sports car or for an asset class that could be higher risk, but we need to make sure that each manager fills a specific role toward attaining the desired asset allocation.
While the car analogy is fairly rudimentary, we have found that eliminating 10–20% of the top and bottom performers within the peer group will typically improve our success in finding managers that outperform their asset class benchmark in the future. This is because the group of top and bottom performers typically includes investment managers that have been investing outside of their product’s stated universe and may, therefore, not be a reliable way to access the targeted exposure. We are always looking for managers that can outperform their benchmark, but our quantitative analysis allows us to detect the source of that outperformance and then avoid investments that have been successful due to non-mandated tilts and embrace ones driven by a repeatable process of generating alpha.
The method of understanding relative and absolute performance is one example of blending art and science in manager selection, but there are many. While we highlight only a very small aspect of our manager selection process in this missive, it highlights several key aspects of our investment philosophy: (1) let the asset allocation direct the selection of investments rather than collecting recent “best performers” or trying to fit a potential fad into the portfolio, (2) identify the investment managers that will best implement the asset allocation goal, (3) build a well-constructed asset allocation that leaves room for many types of investments, including some higher risk ones (i.e. the sports car), (4) refrain from chasing the highest returns and focus on managers with a repeatable process of generating alpha, (5) always understand how the track record was generated and if the current positioning is consistent with the desired factor exposures, and (6) employ experienced professionals that know how to develop quantitative and qualitative analyses, but who also know how to validate and interpret them.
This communication contains the personal opinions, as of the date set forth herein, about the securities, investments and/or economic subjects discussed by Mr. Loeser and Ms. Ouyang. No part of Mr. Loeser’s or Ms. Ouyang’s compensation was, is or will be related to any specific views contained in these materials. This communication is intended for information purposes only and does not recommend or solicit the purchase or sale of specific securities or investment services. Readers should not infer or assume that any securities, sectors or markets described were or will be profitable or are appropriate to meet the objectives, situation or needs of a particular individual or family, as the implementation of any financial strategy should only be made after consultation with your attorney, tax advisor and investment advisor. All material presented is compiled from sources believed to be reliable, but accuracy or completeness cannot be guaranteed.
