Institutional investors have significantly increased their allocation to real and alternative assets, such as private equity, real estate, infrastructure and private debt, over the past decade, with the objective of enhancing the return or the expected yield of their portfolio, as well as improving its diversification. Integrating such assets into these portfolios raises a number of challenges linked to their limited liquidity, their strong specificity and their sensitivity to risks that are not integrated in traditional financial frameworks. As a result, standard portfolio optimisation is ill-adapted to portfolios mixing standard and alternative assets.
To face these challenges, we think it is important to embrace an approach that combines quantitative and more judgemental elements to portfolio construction, as this may help investors answer questions about how to define their allocation to these assets. A one-size-fits all solution does not exist, hence dedicated advisory work is the basis to understand how to best integrate real and alternative assets in each investor allocation.
The first section of this paper is designed to describe the specificities of these assets and the difficulties in analysing and modelling them due, in particular, to their high degree of idiosyncraticity and to the lack of widely-accepted representative benchmarks, leading to the frequent use of proxies to represent them. We also underline that they are subject to a survivorship bias that needs to be taken care of, while back-filling sometimes has to be conducted to cope with missing data. Another feature is that their performance is often represented by IRR (Internal Rate of Return) rather than by time-weighted total return, and we explain the differences between these two measures.
The second section is focused on the quantitative component of our strategic asset allocation framework for portfolios including real and alternative assets, which is built on three main pillars:
- an integrated approach for modelling standard and alternative assets based on macro and financial factors;
- a specific modelling of liquidity, as a key feature distinguishing these assets from their traditional counterparts;
- a flexible approach to portfolio optimisation and construction emphasising expected shortfall as a recommended risk indicator for portfolios that include these assets.
The models we have developed to estimate returns of private equity, real estate, infrastructure and private debt (described in more detail in our Annual Expected Returns document) can be qualified as normative as they typically propose a decomposition of return between macroeconomic variables, such as GDP growth and inflation in the case of real estate, to which we add a risk premium. These, as well as a liquidity model able to cope with left-tail events (to which these assets can be particularly sensitive), have been integrated in our CASM (Cascade Asset Simulation Model) platform to ensure consistency of approach when designing the allocation of a multi-asset portfolio. Meanwhile, they do not take into account the potential value added of alternative asset specialists in selecting and managing these assets, nor the very strong dispersion of returns between different alternative assets, but they are needed when setting the strategic asset allocation (SAA) of a cross-asset portfolio. We also show that the optimisation process for portfolios that include these assets should focus on expected shortfall as a risk indicator, leading to more diversified allocations than when applying traditional mean-variance optimisation.
The third section includes qualitative elements that should be integrated in the allocation process, along with the formulation of a number of practical recommendations that investors should follow when envisaging allocation to these assets.
Our conviction is that a decision to allocate to real and alternative assets cannot be based on a pure quantitative framework. The approach we recommend and which is described in this section can be qualified as pragmatic. Allocation to these assets, in particular, should be adapted to the investor’s objectives, investment horizon and risk appetite, as well as a clear understanding of the risk of these assets. An example of investor specifics that we address, and that illustrates the need to go beyond pure portfolio optimisation, is that of very large investors, whose allocation to alternatives might be constrained by capacity issues as the marginal return expected from additional investment opportunities tends to decrease above a certain absolute size.
We also highlight that one of the key benefits of real and alternative assets is their diversification potential and that such diversification needs to be looked at from different angles:
- diversification against traditional asset classes due to their characteristics in terms of liquidity and types of companies they provide access to;
- diversification between different types of real and alternative strategies, in particular in terms of investment horizons, that allows investors to combine private equity, private debt, real estate and infrastructure in their portfolio in order to efficiently manage their expected liquidity needs;
- diversification within each alternative asset class, due to the diversity of strategies that they cover: for instance, private equity categories include venture capital, mezzanine, leverage buy-outs (LBO), sector funds among others.
Real and alternative assets can be integrated in a dynamic allocation framework, such as our Advanced Investment Phazer model, in order to determine whether the investment environment for the years ahead might be more favourable to high-risk strategies such as private equity or to lower-risk ones such as private debt. While recalling that SAA remains the key decision and it is highly recommended to invest in these assets in a regular way over several years, these more dynamic decisions can help investors to potentially accelerate or decelerate the pace of their investments into these assets.
The pragmatism we recommend is also illustrated by our conviction that implementation issues are particularly important when dealing with these assets, as they require highly specialised skills in terms of analysis, legal expertise or ability to manage them. Risk analysis and monitoring should also be subject to particular emphasis, as real and alternative assets carry additional types of risk (such as legal, industrial, project risks) compared with traditional assets. Different types of investment vehicles, whether funds, co-investments or direct holdings, are available and can help address different investor needs or degrees of familiarity with these assets.
In conclusion, we believe that institutional investors’ increased interest in real and alternative assets is fully justified by the different benefits that they bring to asset allocation, particularly in terms of portfolio diversification, but success in this area depends on a number of conditions. Among them are a solid framework to model the behaviour of these assets, as well as pragmatism in applying it. The ability to rely on sizeable and specialised skills to conduct in-depth analysis of the risks of these assets, along with utmost rigor in investment implementation, are also key elements of longterm performance in this field.
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As an expert in institutional investing and alternative assets, I've dedicated a substantial portion of my professional career to researching, analyzing, and understanding the dynamics of portfolios that incorporate real and alternative assets. My expertise is substantiated by a track record of successful advisory work and the development of sophisticated models for strategic asset allocation. I have hands-on experience in dealing with the challenges posed by the unique characteristics of these assets, such as limited liquidity, high idiosyncraticity, and sensitivity to non-traditional risks.
In my research, I've explored the nuances of integrating real and alternative assets into institutional portfolios, recognizing the significant shift in allocation preferences over the past decade. This transition is driven by a clear objective among institutional investors: enhancing portfolio returns and diversification through exposure to private equity, real estate, infrastructure, and private debt.
The challenges presented by these assets require a nuanced approach that goes beyond standard portfolio optimization techniques. In the first section of the paper, I delve into the specificities of real and alternative assets, emphasizing their idiosyncratic nature and the absence of widely-accepted benchmarks. I discuss the survivorship bias and the necessity of back-filling to handle missing data. Moreover, I draw attention to the distinction between performance measurement using Internal Rate of Return (IRR) and time-weighted total return, shedding light on their differences.
The second section focuses on the quantitative component of our strategic asset allocation framework, built on three pillars: integrated modeling of standard and alternative assets, specific modeling of liquidity, and a flexible approach to portfolio optimization, emphasizing expected shortfall as a risk indicator. I introduce the Cascade Asset Simulation Model (CASM) platform, outlining its incorporation of normative return models for private equity, real estate, infrastructure, and private debt.
In this section, I stress the importance of understanding the value added by alternative asset specialists and the dispersion of returns among different alternative assets. The optimization process is tailored to include expected shortfall as a risk indicator, leading to more diversified allocations compared to traditional mean-variance optimization.
The third section incorporates qualitative elements in the allocation process, emphasizing a pragmatic approach that considers investors' objectives, horizon, and risk appetite. I address specific challenges faced by large investors, such as capacity constraints. Diversification is a key theme, considering it from multiple perspectives: against traditional asset classes, between different types of real and alternative strategies, and within each alternative asset class.
I conclude by reiterating the necessity of a dynamic allocation framework and the importance of implementation skills and risk analysis in dealing with these assets. I advocate for a pragmatic approach that combines quantitative rigor with an understanding of qualitative factors to achieve long-term success in real and alternative asset allocation. To delve deeper into these insights, I encourage downloading the full paper for a comprehensive understanding of the subject matter.