In institutional real estate investment, portfolio managers are typically deal-driven; they meticulously scrutinise various aspects of individual assets when assessing potential acquisitions.
However, aspects of portfolio construction often need more attention.
The ability to intelligently assemble a portfolio of assets to maximise expected returns for a given level of risk is a crucial advantage for managers of balanced funds. However, data challenges and analytical resource constraints have limited portfolio managers’ ability to address this issue quantitatively.
With increased computing power, greater access to machine learning, and generative artificial intelligence significantly reducing analysis costs, there’s an opportunity to rethink portfolio construction. Today, portfolio managers can reframe how they conceptualise diversification, ensuring they consider multiple dimensions of diversification and actively manage risk budgets.
The best way to achieve return goals is to focus on risk, not return. Real estate portfolio managers are increasingly able to do just that.
Achieving appropriate diversification
Diversification is vital because owning various financial assets is less risky than owning just one type. But it is crucial to consider which asset characteristics drive differences in performance.
The most defining physical features of a building are its location and sector, which have become the default ways of categorising properties and assessing the diversification of real estate portfolios.
However, these characteristics only partially explain variations in investment performance. According to MSCI analysis of global real estate funds, sub-market allocation represented just 30% of the tracking error of real estate portfolios relative to their benchmarks between 2008 and 2019. Most of the tracking error was attributable to other factors.
Portfolio managers do act with an awareness of other variables when constructing portfolios. For example, they try to ensure diversification by the year of lease expiry, knowing that reletting risks depend on the economic conditions when a property becomes vacant. They also recognise that investor interest in assets with varying lease lengths fluctuates throughout different stages of the real estate cycle.
Further, many portfolio managers seek to avoid excessive dependence on rental income from a single tenant or specific industry, although optimising such diversification efforts is challenging.
Fewer, however, focus on asset quality, which drives performance variation through the cycle. For instance, better-quality assets are typically easier to lease with less rental discount during market downturns. In contrast, lower quality assets with cheaper rents may outperform when occupiers become more cost-conscious as the cycle advances.
A deeper understanding of how diversification benefits a portfolio can enable managers to assess the impact of potential acquisitions on both risk and return. Portfolio managers can utilise machine learning engines to identify the factors that have historically driven a portfolio’s performance and inform intelligent assumptions about future sources of diversification.
Risk budget management
Understanding the risk characteristics of each asset also enables assessing how effectively a risk budget is utilised. Risk budgets are an under-discussed concept in private real estate. Suppose the appropriate overall amount of risk exposure for a mandate is known, and the riskiness of individual assets can be measured; in that case, judging whether a mandate is exposed to too much or too little risk becomes possible.
Historically, a typical approach for real estate portfolio managers has been exclusively targeting assets with risk and return characteristics consistent with their mandate. For example, a core-plus fund targets core-plus assets exclusively. This approach is driven by practicalities, suc as the limit to how many assets they can review and the need for transaction teams to have firm guidance from fund managers. However, this approach fails to adopt a comprehensive portfolio perspective.
Towards a portfolio approach
A portfolio must deliver on a specific return objective, but there is scope to include assets with various risk-return profiles within the same portfolio. Portfolio managers should not define their investment universe too narrowly.
Previously, managers constrained their universe to match the limited resources available for prospecting and underwriting. Now, with greater compute power and accessible AI, the analysis costs have been radically reduced. So, there is scope to consider a much larger opportunity set. By casting a wider net, investment managers increase their chances of finding mispriced assets. At times, better value may be found in different parts of the risk curve.
Furthermore, diversifying by risk characteristics can be an effective form of diversification. Higher-risk assets are likely to perform differently than lower-risk assets. For instance, secondary asset performance might depend more on occupier market fundamentals and economic growth, while prime assets with good income security may be more sensitive to interest rates. Achieving diversification by interest rate and growth sensitivity – the two key drivers of real estate performance – is particularly beneficial.
Focus on risk to achieve your return goals
Technological advances are creating new opportunities to gain an advantage through superior portfolio construction. Appropriate diversification allows for higher returns for a given amount of risk. Embracing the concept of risk budgets enables portfolio managers to survey a broader opportunity set, increasing their chances of finding assets that offer excess returns while achieving the diversification benefits of holding assets with different risk profiles.
Start leveraging these technological advancements today to enhance your portfolio’s performance.
