Manager Evaluation & Due Diligence

Investment Education
Manager Evaluation is a critical part of investment portfolio due diligence. Having a framework to evaluate managers can provide a clear path to better understanding their performance and setting expectations.

Part 1

Where to start with manager selection

The first place to start when it comes to manager selection is often not with the manager at all, but rather the investment objective you are looking to achieve. For example, are you looking for exposure to global bonds? Perhaps a market neutral mutual fund with strong value exposure? Maybe a global multi-asset alternative? What about digital assets?

Once you know the investment objective, it’s time to begin surveying the landscape for managers who provide those exposures and to begin a manager selection process. 

Part 2

Why is manager evaluation important?

Successful manager due diligence can align expectations and reduce uncertainty. This is true in a variety of ways, as many choose to use investment managers for different parts of their portfolio. This can range from Large Cap US equities, all the way to global multi-asset sleeves. However, the differences between managers go beyond just investment objectives, as even two Large Cap US equity managers can have vastly different approaches. For example, one may favor quality stocks while another favors risky value. This difference will change expectations as to when these strategies are expected to outperform relative to their benchmark. 

Because investment managers can be so differentiated, they must be considered in parallel with investment objectives. The more thorough due diligence investors conduct on managers, the less likely they are to be surprised by their results. This can increase the cohesion of an investment strategy and provide conviction amid volatility. 

Part 3

The role of qualitative and quantitative manager due diligence

Both qualitative and quantitative evaluation frameworks of managers are typically a part of investment due diligence, and rightfully so.

Qualitative insights such as meeting or surveying a manager can provide valuable information about their approach. This includes learning about the culture and depth of their team, as well as the history of their strategy and management. This can add important context to historical and future performance. 

Quantitative analysis, we would argue, is equally, if not more important. Quantitative analysis helps to connect the dots of what a manager says and what they actually do. This includes evaluating risk and return patterns, diversification benefits, and scenario analysis. 

There are limitations to some quantitative analyses, however. Looking at past risk and returns only explains “what happened” and not the “how”. This is why we believe factor analysis can be a powerful tool to amplify manager due diligence. Factor analysis decomposes risk and provides insight into what drove performance. Learn more about Factor Analysis here. 

Part 4

Manager evaluation with the added lens of factor analysis

A thoughtfully chosen and constructed risk factor lens can provide transparency into what is driving the risk and return of individual investments and portfolios. For example, Venn's Two Sigma Factor Lens measures fund manager performance through a curated and independent set of common factors, allowing for a deeper understanding of what is driving risk and return. Factor-based manager evaluation can be conducted on anything with a return stream, including private investments, liquid alternatives and registered fund managers. 

For example, Venn’s analysis of the Vanguard Market Fund conducted in 2020 found that for over 20 years the fund was successful in providing little to no exposure to equity or bond markets. It did, however, have over 25% of its risk explained by the momentum equity style, which led to over 2% of annualized return. This result is not inherently bad or good, but undoubtedly important for the investor to consider when conducting manager due diligence in concert with their overall portfolio.

Read our FAQs on our Two Sigma Factor Lens.

Part 5

The importance of trends in manager performance and risk

When conducting manager due diligence it is important to view data in rolling periods over shorter time frames, including rolling factor analysis. This helps paint a picture of what risks the investment was exposed to over time, and how those exposures may have changed. 

This can help uncover various insights that might otherwise be hard to pinpoint. For example, how did fund performance change when managers changed? Have they changed their risk profile over time? Has the strategy adapted or stayed the course in distressed markets? Has the manager achieved their results by being true to their investment mandate, or have they deviated by obtaining exposure to other risks?

Is the manager investing according to their stated mandate?

A common Venn use case is reviewing a manager’s factor analysis output to try and better understand their style and approach. Sometimes the output can help confirm one’s understanding of what the manager is doing, and other times it can lead to questions. 

An example of the latter case may be a manager that says they invest in stocks based on value characteristics, but factor analysis output indicates a zero or even negative value factor exposure. This is known as style drift, which can sometimes be a welcomed manager characteristic, but also can be seen as problematic if they do not provide the intended exposure. Given this, an investor may want to dive deep into what is driving that result and whether or not that style of investment management meets their expectations.

Part 7

Is the manager providing value?

Venn's Two Sigma Factor Lens is holistic, in that it aims to explain as much risk as possible in institutional portfolios. However, there are often elements of an investment’s return stream that are idiosyncratic and can’t be explained by common risk factors. This is also known as residual return. 

With that being said, residual return may be thought of as a manager’s alpha, or their unique manager skill. As a result, it can be helpful to analyze how much residual is contributing to overall risk and return, and whether that residual is positive or negative.

Similar to analyzing factor exposure over time, analyzing residual over time can also provide valuable information. Sometimes a manager may have a high positive residual that fades over time. This may indicate that their investment style has become less effective or fallen out of favor. Sudden changes in residual may also mark important moments in the fund’s history, such as a change to the manager or stated investment approach.

Part 8

How to compare fund managers

Comparing fund managers is often a matter of laying quantitative or qualitative analysis side by side to better understand how, when, and why the managers have been different. 

For example, it is quite possible that one manager took on more risk to achieve a similar return, which may make them less attractive for risk averse investors. Or perhaps one manager has had consistently more risk, but has shown the flexibility to change strategies when the market was in severe drawdown to better mitigate on the downside.

In a similar regard, one manager may have outperformed another, but factor and residual analysis of their returns shows inconsistency. Perhaps one manager has had strong exposure to a factor that has happened to be in favor, but your view is that such a factor may underperform going forward. 

These questions aim to look through surface-level analyses such as which manager had lower risk or higher return, and instead paint a fuller picture. Knowing more of the story behind manager performance can help create realistic expectations, which may lead to more informed decision making.

Part 9

How does a manager fit into your portfolio

Evaluating a manager on a stand alone basis is often the first step, but it is important to consider whether that manager is (or would be) redundant or diversifying within your current portfolio. Managers with different investment objectives might actually possess similar underlying factor exposures. This may lead to a high correlation of their returns over time, signaling that the addition of said manager may not actually be adding to portfolio diversification.

If, hypothetically, two managers were equally additive after conducting your due diligence, it is likely that the manager that is least correlated with your portfolio would provide the most benefit through added diversification. Using tools such as Venn, you can even analyze these correlations among individual holdings or sleeves of your portfolio, making sure that you are diversified in US equities or international fixed income, for example. You can also analyze diversification benefits of a manager’s residual returns, to hypothetically understand which unique aspects of each manager are most diversifying.

It is worth noting that allocators may have a better understanding of their views at the portfolio-level rather than manager level. As a result, using tools that promote actionable insights can also be helpful when evaluating a manager in the context of your portfolio. An example of this would be how Venn allows users to source contribution to portfolio-level risk at the individual sleeve, manager or asset level. Thus, it can be helpful to think about managers in the context of how effectively they are helping to achieve overall portfolio strategy, with quantifiable data to support it.

Part 10

Tying it all together

Manager evaluation is a critical part of any investment process that utilizes them. While we believe in both qualitative and quantitative analysis, quantitative due diligence often provides the most transparency. At Venn, we amplify standard manager due diligence workflows with factor analysis, helping investors to understand the details of what has driven risk and return, and allowing for head-to-head comparisons. Venn's factor analysis also enables important additional workflows, such as forecasting, trend and scenario analysis, as well as optimization.

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