AssetMetrix’s Factor Benchmarking module for private capital funds

Factor benchmarking for private capital funds

A simple introduction to factor investing 1

When you want a healthy body, you need to know what you eat. Therefore, to better understand your diet, you check the nutrition statistics of the groceries you buy. When analyzing your Private Capital portfolio, this concept can be applied in a similar way: For a healthy portfolio, you need to know what drives your performance. According to this analogy, you check your portfolio’s factor exposure to understand its underlying return ingredients (= components = factors).

Our Factor Benchmark module shows you the public components (= ingredients = factors) of your private portfolio returns. This enables you to identify a more suitable public market benchmark than just the MSCI World index (or any other broad public market index). Thus, our Factor Benchmark module is a more sophisticated version of traditional Public Market Equivalent (PME) benchmarking which uses only a single reference index, as it incorporates additional non-diversifiable risk factors. In other words, factor benchmarking aims at finding the most suitable benchmark for a given portfolio, since it is risk-adjusted.

In turn, if you just use an equity index as the benchmark, you implicitly assume a market beta factor of one and neglect all other potential risk factors. Our Factor Benchmark module goes beyond that and reveals the public performance and risk drivers that are usually hidden from you.
Using one-dimensional benchmarks that ignore these factors might become more problematic in the future, as already in 2021 “some 62% of institutions with more than $200 billion of assets have put factors at the heart of asset allocation”. Especially when you pay high fees for active management, you want your investments “to add value beyond factor exposures that you can access relatively cheaply”. 1 These are two strong arguments that public factor benchmarking will also emerge as industry standard in the Private Capital industry. In the future, GPs who can prove that they understand their fund’s factor exposure might find it easier to attract investors. On the other hand, LPs (asset owners) will demand this information about their private portfolios more frequently and insistently.
From our experience, we find that currently even renowned industry experts often struggle to interpret and apply factor investing insights in the Private Capital context.

1 Both quotes from: MSCI Investment Insights 2021, Global institutional investor survey, pp. 24-25.

The factor methodology 2

To seamlessly include Private Capital portfolios in a factor investing framework, the AssetMetrix Analytics team has developed a unique and innovative Factor Benchmark module. Our factor approach follows a linear multi-factor model,

    \[  E(R_{PE}) = R_{RF} + \sum_i \beta_i \cdot E(R_i) \]

which is just a simple extension of the famous Capital Asset Pricing Model (CAPM) formula.

E(R_{PE}) is the expected private equity return, R_{RF} is the risk-free rate, \beta_i is the beta factor for the ith factor, and E(R_i) is the expected return of the ith factor. In our case, we regard the Market Excess Return, the Size Factor, the Value Factor, the Quality Factor, and the High Dividend Yield Factor as potential factors that can explain your private portfolio return i \in {MKT-RF,SIZE,VALUE,QUALITY,HIGH DIVIDEND}.
The factor choice is grounded on academic insights (Market, Size, and Value are established within the popular Fama-French model) and standard industry practices (Quality and High Dividend Yield are commonly used by practitioners). To determine your portfolio’s beta coefficients, we select the factor exposure that best describes your observed portfolio cash flows from a pre-calculated coefficient ensemble (that has been estimated on a broad Private Capital dataset).

The new Factor Benchmark section in the AssetMetrix portal 3

A closer look at our Factor Benchmark module reveals that it can be broken down in three parts:

1) Factor Exposure

The Factor Exposure table shows you which public factor exposure best explains the cash flow profile of your Private Capital portfolio (and sub-portfolios).

Figure 1: Extract of the Factor Exposure table

Figure 1 lists the factor values for an exemplary portfolio. It can be read as follows: A “Risk-Free Rate” builds up the baseline; therefore, its coefficient is always 1. The “Market – Risk-Free Rate” value of 1.27 shows that this portfolio is located 0.27 above the market beta of 1. This means the market risk factor is 27% higher for our given Private Capital portfolio than in the public market portfolio. Consequentially, the expected return attributed to the market factor also has to be 27% higher for our private portfolio since investors always want to be compensated for bearing systematic risk. To better understand how to interpret the remaining four factors, we take a look at the following Figure 2.

2) Factor Explanation

The factor explanation table shows you how to build the factors (via one long and one short position of MSCI style indices) and exhibits the historical returns associated with these factors. As all long and short positions from Figure 2 are publicly investable (e.g. via ETFs), the coefficients shown in Figure 1 can be interpreted as a “recipe” for how to construct the public benchmark portfolio that best replicates your Private Capital portfolio. Therefore, coming back to the nutrition analogy from the introduction, the long and short positions in Figure 2 better define the factors’ underlying “ingredients”.

Let’s look at some examples.

Figure 2: Extract of the Factor Explanation table

The above stated “Size Factor” value of 0.14 (cf. Figure 1) indicates that the example portfolio positively trends towards the MSCI Small Cap rather than the MSCI Large Cap (cf. Figure 2). The negative “Value Factor” of -0.30 (cf. Figure 1) means that the portfolio return is better described by the MSCI Growth than by the MSCI Value. The same logic holds for the “Quality Factor” and “High Dividend Yield Factor”. Thus, the long and short position information allows a mapping between your Private Capital portfolio and public equity indices which facilitates holistic asset allocation across asset classes.

Our full Factor Explanation table also gives you concrete figures on public market returns of the last x years (in this example 5, 10, and 15 years).

In addition, the Factor Return Decomposition (3) visually breaks up the return contributions of each factor in different time periods. Here, the beta coefficients from Figure 1 are multiplied by the corresponding realized returns from Figure 2.

Figure 3: Extract of the Factor Return Decomposition Chart

In the example from Figure 3, we see that the “Market – Risk-Free Rate” factor accounts for about half (50,82%) of the realized return within the last five years. The second most important factor is “Value” which accounts for about one quarter (25,91%) of the realized return in this period. In this specific example, the “High Dividend Yield” factor exposure actually lowered the realized return by a small amount (-2.14%). In this context, it is important to keep in mind that the chart shows return proportions which add up to 100% to better highlight the relative factor importance.

Our solution is flexible, adjustable, and customizable to your needs. For example, we can perform the analysis also on segments of your Private Capital portfolio, i.e. different groupings according to Fund of Funds, Regions, Programs, etc. As a starting point, we chose four factors that are well-established, especially in the liquid markets (Size, Value, Quality, and High Dividend Yield). Nevertheless, we are continuously enhancing the solution and are happy to discuss more tailored applications that allow for even deeper insights.

In sum, AssetMetrix’s Factor Benchmarking module enables you to improve your decision-making by providing a sophisticated public benchmarking metric accessible for your Private Capital portfolio considerations.

The MSCI information may only be used for your internal use, may not be reproduced or redisseminated in any form and may not be used as a basis for or a component of any financial instruments or products or indices. None of the MSCI information is intended to constitute investment advice or a recommendation to make (or refrain from making) any kind of investment decision and may not be relied on as such. Historical data and analysis should not be taken as an indication or guarantee of any future performance analysis, forecast or prediction. The MSCI information is provided on an “as is” basis and the user of this information assumes the entire risk of any use made of this information. MSCI, each of its affiliates and each other person involved in or related to compiling, computing or creating any MSCI information (collectively, the “MSCI Parties”) expressly disclaims all warranties (including, without limitation, any warranties of originality, accuracy, completeness, timeliness, non-infringement, merchantability and fitness for a particular purpose) with respect to this information. Without limiting any of the foregoing, in no event shall any MSCI Party have any liability for any direct, indirect, special, incidental, punitive, consequential (including, without limitation, lost profits) or any other damages. (

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Christian Tausch

Dr. Philipp Abel
Product Development

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