Over-reliance on geographic, sector and style labels and an emphasis on volatility of total returns could be misleading investors. Matthew Richardson explains
The traditional approaches to decision-making in direct real estate could arguably be improved. Two problems in particular are worth noting:
• There is over-reliance on geographic, sector and style labels; such labels, while useful in many ways, can mislead because they fail to capture the true risk of real estate assets;
• Too much emphasis is placed on the volatility of total returns; total returns data mask the marked difference between the volatility of income returns and capital returns.
Better results are obtainable by looking through sector, geographic and style labels at the underlying cash flows, although this is more challenging. The difference in volatility of income returns and capital returns merits far greater attention.
It is acknowledged that these changes being advocated are radical and will take time to achieve. It is also recognised that decisions need to be made using the data and techniques that are currently available, so practical suggestions relating to the identification of the sources of return, risk and diversification have been included.
Currently, real estate assets are largely categorised according to familiar style labels (core, core-plus and opportunistic) and according to sector or geographic descriptions (such as German retail or London office).
There is an overriding question about just how effective and useful these labels are with respect to the key objective of generating good risk-adjusted returns.
A widely used measure of risk-adjusted return in the equities world is the Sharpe ratio. This deducts an appropriate risk-free rate from the expected return of an asset to get a measure of excess return. This excess return figure is then divided by the standard deviation or volatility of the asset in order to obtain a risk-adjusted return figure.
The Sharpe ratio effectively provides a measure of return per unit of risk – analogous to the miles-per-gallon or kilometres-per-litre measure that will be familiar to any driver. When making choices based on the Sharpe ratio, a higher result is better.
Another useful measure of risk-adjusted return is the ‘coefficient of variation’ or ‘unitised risk’. This measure divides the standard deviation or expected volatility of an asset by the expected return to get a measure of risk for a given unit of return. Using the car analogy again, this would be similar to gallons-per-mile or litres-per-kilometre. When making choices based on unitised risk, a lower result is better.
In the following analysis, we show that the long-term income return of real estate assets has been higher than the capital component. We also show that the volatility of the income return has been considerably lower than the capital component. We conclude from this that the risk-adjusted return of the income component is superior to that of the capital component.
To answer the earlier question, we need to look closely at long-term real estate returns and the key sources of volatility. When we analyse historic data, one consistently clear finding across mature real estate markets is the primacy of income returns in terms of driving overall long-term returns.
Figure 1 shows the components of total return in US real estate over the decades since 1930, illustrating both the dominance and stability of income returns. The income returns shown in figure 1 are both higher and less volatile than capital returns. The same points made about figure 1 are also evidenced in figures 2 and 3, which both show UK data for the period from 1981 to 2012. In the UK, the average income return over the period from 1981 to 2012 came at the expense of a standard deviation of +/-1%. On the other hand, the capital return over the same period had a far wider associated standard deviation of approximately +/-10%.
In terms of institutional investors seeking good risk-adjusted returns, the message from this analysis should be clear: income returns matter more than capital returns and are vastly more reliable. Other things being equal, then, for any given level of expected return, an asset that relies more on capital growth to deliver its target return is likely to be a riskier bet in the real estate context.
Another way of saying this is that the cash flows arising from future capital gains are less certain than income, so investors are likely to get better risk-adjusted returns whenever there is a greater reliance on income as opposed to capital growth to achieve a target return.
Geography and sector labels are crude measures for assessing risk, return and diversification. The above insights represent a challenge to the prevalent industry approach of relying on risk labels. More specifically, the traditional approach tends to assume that geographic diversification is the key measure for achieving portfolio diversification.
If we accept that income return is actually the prime driver of long-term real estate returns, then geography should matter only to the extent that it influences the income and cash flows, which in turn will be influenced by factors such as prevailing lease structures, local taxation and business practices.
Of course, this is not the same as saying that geography is inconsequential because we know that local economic factors, political factors and obsolescence patterns can influence cash flows and income.
Another issue with the current labelling method is its lack of flexibility in reflecting the true risk of assets over time. In particular, the risk level of assets changes over time, so class definitions that are based on geography or sectors are unlikely to capture such changes.
A new office building in 2003 did not have the same risk profile as the same 10-year old office building in 2013: the asset is physically different, the local occupier market is different and the investor market is different – yet the label is the same. To be useful for decision-makers, real estate labels needs to be flexible in ways that reflect such risk profile changes.
Geography is not always a suitable measure of risk and return, as a simple analysis of the Frankfurt office market illustrates. Figure 4 shows total returns by asset in 2011. The dispersion between the best and worst performing asset is 33%, while the average return is 2.4%.
Similarly, sector is a rather arbitrary means of measuring diversification. Again, sector type does have an impact on asset-level or fund-level risk and returns because different property types are subject to differing lease structures, taxes, tenant types and local economic conditions.
In a world where risk is dynamic and where, generally, more risk is associated with the capital rather than income component of real estate returns, the current labelling approach based on geographic and sector distinctions is not ideal. Instead, investors should decide on their desired risk-return appetite and then focus on acquiring assets that provide the cash flows to match.
When comparing alternative assets, the primary focus should be on expected cash flows and the risks associated with these cash flows rather than on total expected returns. We would call such an approach a ‘structured income approach’ to decision making.
In an ideal world, the best structured income approach would be a stochastic cash-flow approach where all expected cash flows are assigned probabilities based on a range of different possible scenarios and modelled using Monte Carlo simulations.
To appropriately determine the probabilities that should be attached to future cash flows, real estate practitioners need to understand all the risks that are associated with those cash flows. Two key areas that are often overlooked and under-researched are tenant risks and lease risks.
• Tenant risks: While much of the industry’s focus is often on inherently difficult-to-know areas such as expected capital growth levels, other areas, where valuable hard data are often available, can be neglected. One such area, which can obviously impact future cash flow, is the ability of the tenant to pay the rent. In particular, a better assessment of the likelihood of tenant default can often be made by looking at publicly available credit information on the company.
• Lease risks: The other widely overlooked determinant of property performance is the lease structure. The lease is effectively the legal agreement that shapes how cash is released over the life of the investment. For example, the stability of cash flows can be significantly affected by the landlord’s ability to review rents at appropriate times, their ability to switch tenants and whether leases contain provisions for upward-only or index-linked rent reviews.
There is considerable variation in the rules and market practices relating to leases. Consider, for example, the difference between rent-free periods in the UK and Germany (figures 5 and 6). In the UK, the average rent-free period is 12.7 months whereas in Germany it is 4.2.
Our assertion is that genuine long-term diversification is more likely to be achieved through a combination of complementary income sources and lease structures than through naive geographical or sector diversification.
By applying probabilities to each of the events shown in figure 7, investors could determine risk-adjusted cash flows that could be used to identify potential disruptions to future returns.
This means that effective fund investment should actually be driven in large part by seeking to mitigate these kinds of risks at the fund and asset level rather than by making ‘calls’ based on location, on sector or on market timing.
Having multiple lease structures, varied lease lengths and careful staggering of the key lease events allows cash flow interruptions to be minimised. This structured approach to cash flows smooths income over time and should also help to lower capital value volatility.
Looking beyond the labels to estimate underlying cash flows can take time and research, and decision-makers often operate under time constraints. We recognise that choices need to be made based on the data and techniques that are currently available; therefore, we suggest some practical suggestions relating to the identification of sources of return, of risk and of diversification.
Capital returns are much more volatile than income returns, so the range of outcomes associated with strategies that rely heavily on capital gains is wider. Investors pursuing strategies that require substantial capital returns should therefore undertake rigorous due diligence before making their initial investment and continue to monitor assets closely once a transaction has been closed.
By contrast, the range of outcomes associated with strategies that rely mostly on income return is relatively narrow. While all investment choices require extreme vigilance, those with the widest range of outcomes naturally require more.
There are some key guidelines that investors should be aware of. When pursuing target returns that significantly exceed initial yield, be prepared to spend a lot of time on due diligence. Try running mean variance optimisation exercises, treating real estate income returns and capital returns as if they were separate asset classes. This should be helpful in terms of illustrating the difference between income-reliant and capital gains-reliant strategies.
Investors should first decide on their desired risk-return appetite and then focus on acquiring assets that provide the cash flows to support this. Quantifying risk is not easy and it is always tempting to focus mostly on return, potentially leading to bad decision making.
When assessing the risk-return ratios of different investment options, it is preferable to use the coefficient of variation (risk per unit of return) rather than the Sharpe ratio (return per unit of risk). Both measures will tend to point in the same direction for static choices (A versus B) but the former is better for comparing the relative riskiness of changes (for example, A moving to B versus C moving to D).
Strategy A will improve the portfolio’s Sharpe ratio from 0.2 to 0.3 whereas Strategy B will improve the portfolio’s Sharpe ratio from 0.6 to 0.7. Which strategy reduces risk most? The intuitive answer is that both strategies have the same effect, given that the change in Sharpe ratio is 0.1 in each case. However, Strategy A is far better at reducing risk because risk reduction is not linear.
Moving from a Sharpe ratio of 0.2 to 0.3 drops the risk level by 33% whereas moving from 0.6 to 0.7 drops the risk level by only 14%. This is much easier to understand if the CV (unitised risk) measure is used.
For those pursuing good risk-adjusted returns in real estate markets, the traditional approaches to decision making are open to improvement. There is too much focus on sector, geographic and style labels and on total-return volatility. Labels can be misleading and total return volatility masks the marked difference between the volatility of income returns and capital returns.
Assets that derive proportionately more of their total return from income as opposed to capital gains are likely to be more reliable from a risk-adjusted perspective. Conversely, strategies that are heavily reliant on capital returns to meet their return target are likely to be more volatile.
Volatile strategies expose investors to a wider range of potential returns and therefore naturally demand a higher governance budget (in terms of both time and money).
The prevalent focus on the location and sector descriptions of assets (as evidenced in the labelling of many funds) is ineffective at capturing the true risk of real estate assets, which is dynamic rather than static in its nature. Instead of necessarily fixed geographic labels, labelling nomenclature should be flexible to reflect the changing risk of different assets.
It is acknowledged that the changes advocated could be seen as radical and will take time to achieve. In the interim, we offer three practical tips that should help to improve the decision-making of real estate investors. If pursuing target returns that significantly exceed initial yield, expect a wide range of outcomes and set aside lots of time and resources for due diligence; when assessing and implementing risk-return ratios, use the coefficient of variation (risk per unit of return) rather than the Sharpe ratio (return per unit of risk). Treat real estate income returns and capital returns as if they were separate asset classes for the purposes of mean-variance optimisation.
Matthew Richardson is director of research, European real estate at Fidelity Worldwide Investment