‍This article was first published by Citywire Switzerland on January 2, 2025.

To make or to buy is a question that regularly presents itself in the wealth management industry. As a sophisticated and demanding clientele expects multi-family offices to deliver holistic solutions covering a wide range of asset classes and strategies, the selective outsourcing of investment management activities is naturally an essential part of the work of professionals in the space.

Independent wealth managers and multi-family offices typically focus on offering one-stop solutions to a demanding clientele. This regularly obliges relatively small teams to cover a wide range of asset classes to come up with holistic investment solutions that not only fit the clients’ needs, but also cater to individual tastes and preferences.

The result is often a combination of internally managed products (e.g. conviction lists or proprietary funds and AMCs) and third-party funds. The latter may sometimes sound trivial but come with important challenges and limitations, which this article explores.

When looking for externally managed active funds, especially in the liquid alternatives space, we typically gravitate towards systematic strategies.

Quantitative strategies, by definition, come with the advantage of a well-defined investment process, reducing the risk of encountering a track record that is merely based on the gut feelings of a few portfolio managers.

More importantly, when constructing a portfolio, it is of utmost importance to us to precisely understand the risk exposures we are getting through every single product.

Consequently, these two aspects are key determinants of our investment process in selecting quantitative funds; a process which itself is based on a combination of quantitative and fundamental analysis.

The quantitative part comprises a detailed dissection of a manager’s track record.

We always insist on obtaining daily data on past performance, which we feed into our proprietary performance analyser, which is an application that allows us to efficiently calculate key performance indicators and perform a wide range of comparisons.

This starts with the strategy’s performance since launch. In this context, we pay a lot of attention to potential indicators of alpha decline.

For instance, we look at the relative performance against various benchmarks (such as relevant indices, ETFs or other comparable funds) as well as rolling returns, volatility and Sharpe or Calmar ratios over different time horizons.

Aside from understanding a strategy’s realised risk-return profile, both on an absolute basis as well as relative to comparable strategies, we are especially interested in the distribution of returns and their correlation to other products and asset classes.

Particularly in the liquid alternatives space, classical indicators like the Sharpe ratio are often not very meaningful as returns may be far from normally distributed.

Some systematic strategies generate steady, low-volatility returns over extended periods but are heavily exposed to tail risks. To address this problem, we examine measures like kurtosis and skewness of returns and pay particular attention to the depth, length and timing of drawdowns.

Additionally, performance decomposition, including regressions on common risk factors and benchmarks, helps us to distinguish true alpha from beta and to answer questions such as the following:

• How reliably can the performance really be attributed to the specific underlying source of return which the strategy tries to capture?
• Does the strategy demonstrate desirable characteristics such as convexity that can provide resilience in turbulent markets?

We find that the purely quantitative analysis, especially the dissection of correlations and exposure to well-known risk factors, can typically reveal a great deal of information on a strategy already, notably if there is a sufficiently long track record.

However, the hard work comprises developing a thorough understanding of the manager’s precise investment strategy and day-to-day implementation. Again, we tend to prefer pure-play strategies that are suitable as building blocks in a multi-asset portfolio over products that combine multiple strategies.

Nevertheless, even analysis of a distinct strategy can be tricky and typically involves several calls and/or on-site visits to get to the bottom of methodologies and conceptual frameworks employed by the manager.

While analysing a strategy’s historical track record allows us to understand to what degree it produced returns in the past, fundamental research attempts to answer the crucial question of why it should continue to do so in the future.

At the heart of each investment strategy, we need to find some kind of explanation for its return-generating ability, rooted either in a risk premium, liquidity provision, or behavioural finance (even though we tend to distrust the latter).

Repeated interactions with the responsible managers and examination of their presentations, white papers, and other materials allow us to get an impression of their degree of sophistication and the diligence, prudence, and care with which the strategy is implemented. There are several common questions we are always interested in:

• In which programming languages are the procedures generating signals written?
• Are calculations run independently on several systems?
• What’s the degree of automation for both signal generation and trade execution?
• How much leverage is taken, how are different risks managed, and which are the main counterparties?

Notably, near the end of the selection process, we always involve several members of our investment team to ensure that we don’t miss or misinterpret any important issues.

Beyond that, we pay a lot of attention to the size and composition of the team, its members’ backgrounds, and tenure, as well as incentive alignment through key personnel’s own investments in the product.

Key man risk may be less of a concern once a strategy is thoroughly set up. However, its continuous development and adaption to changing market conditions, backed by credible research capabilities, remain important factors when judging whether successes can likely be repeated.

When comparing our approach to selecting quantitative strategies with the process used for fundamental managers, one key distinction stands out. With quantitative, the focus is even more on the team and robust systems and processes rather than individual brilliance.

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‍This article was first published by Citywire Switzerland on January 2, 2025.