Despite their different characteristics, new research has found little differentiation between the long-term performance of value-added and opportunistic funds

Some investors in closed-end real estate private equity funds use fund class labels – core, value-added and opportunistic – to help construct portfolios. Differences in fund risk can derive from investing in different property types, geographies, stages of building life and leverage, as well as the degree of fund focus in these areas and the timing of investment decisions by managers. Therefore, it is not clear how useful broad classifications of fund risk are for portfolio decisions when the variety of investment strategies is so large and their execution by managers is so critical. 

Despite the fact that classes of funds differ in investment composition, we show that class has not been a reliable differentiator of performance between value-added and opportunistic funds. In our review of individual fund histories from vintages between 1980 and 2008, average performance does not differ between the two classes. This holds overall, for different periods, and for different metrics of performance. To vet funds, investors should more specifically evaluate fund strategies and management quality. 

To look at fund class and performance, we use data from Burgiss on the class, characteristics and performance of 706 funds raised over the past 30 years, composed of value-added and opportunistic funds.

Figure 1 shows the funds in our sample represent just over $440bn (€340bn) in capital raised between 1980 and Q3 2013. Nearly one-half of the committed capital over this period was raised between 2005 and 2008, and nearly one-third was raised after 2008. 

1. Burgiss REPE data committed capital by vintage year and class

In essence, fund class labels are intended to quantify low, medium and high-risk real estate investment strategies, and target returns are typically interpreted as gross returns. While the precise delineation of expected returns may vary, most real estate professionals will agree on the relative ranking and strategies assigned to each class. 

The general expectation is that core investments are in stabilised properties with low leverage and a focus on income generation from existing rent rolls. Value-added investment involves additional management expertise to re-lease, reposition or redevelop existing assets. Value-added funds may also use greater leverage than core investments. Opportunistic strategies are expected to undertake greater investment in land and development, distressed properties or properties in emerging markets, with perhaps yet another increment of leverage. 

A corollary to these descriptions is that riskier strategies focus less on current income and are more reliant on pricing (or appreciation) to generate returns. In what follows, we rely on Burgiss definitions of class, which are consistent with industry standards.  

Characteristics of funds by class 
First, we examine ways in which value-added funds have differed from opportunistic funds in terms of size and focus on geographies, product types and development. A main difference among fund classes in our sample is fund size. Value-added funds raised $447m in committed capital on average, while the average size of opportunistic funds was $746m. Average fund size for both value-added and opportunistic funds has generally been increasing since the 1980s. 

Geographic focus was also correlated with fund class in this sample (figure 2). Eighty per cent of value-added funds focus on North America, whereas the rate was 62% for opportunistic funds. A main difference between classes was that 14% of opportunistic funds focused on Asia. 

2. Geographic focus - 706 funds - by class

For a subset of 123 funds focused on North America for which we observe holdings data, nearly 60% of value-added funds focused investment in a particular region of the US (figure 3). We call a fund ‘focused’ in terms of US geography if more than 50% of its investment was in one of four regions (East, South, Midwest and West). Only 26% of North-American focused opportunistic funds concentrated investment in just one region. 

3. US geographic focus - 123 funds

Using the subset of all funds for which we observe holdings (183 including funds focused outside of North America), the majority of value-added funds were likely to be highly focused in a single product type, investing more than 75% of committed capital to that type of property (figure 4). Only 16% of opportunistic funds were so highly focused. An additional 23% of value-added funds focused between 50% and 75% of their investments in a single property type. For opportunistic funds, this proportion was nearly 40%. Within this medium category of focus, almost one-half of opportunistic funds ventured beyond office and industrial property to focus on residential, retail, land or hotels as their primary area of investment. Overwhelmingly, focused value-added funds invest in office and industrial property types. 

4. Property type investment focus

Using a simple measure of whether the underlying holdings are operating assets versus development projects, figure 5 shows that nearly 30% of value-added funds placed more than 10% of their investments in development projects, while about 60% of opportunistic funds did so. In comparison to core funds, which typically minimise exposure to development, it is interesting to note that nearly 50% of all funds that we examine (both value-added and opportunistic) allocated more than 10% of their investments to development. 

5. Development focus

Overall, we find that value-added and opportunistic funds historically have differed in the composition of investments. Opportunistic funds were larger than value-added funds, less focused on specific property types and US geographies, and were more international. Opportunistic holdings were more likely to deviate from a focus on office and industrial properties, and they also had a more significant investment in development as compared to value-added funds. The next question we ask is whether these characteristics translate into observable differences in fund duration and performance. 

Before moving to a discussion of fund performance, we first investigate fund duration by class since alternate strategies may result in longer or shorter periods in which capital is effectively employed. For a sub-sample of resolved funds – funds with remaining net asset value (NAV) of less than 2% of fund size – figure 6 shows that average fund duration was quite similar between value-added and opportunistic funds. When we reduce the influence of outliers by looking at the medians, we find that value-added funds had a longer median duration of 5.5 years as compared with 4.25 years for opportunistic funds. 

6. Fund duration.

Performance 
Using the Burgiss fund-level cash-flow data, we are able to follow fund performance through the third quarter of 2013 for vintages beginning in 1980 through to 2008. By truncating our sample after the 2008 vintage, we allow sufficient time to observe investment performance. The 2008 vintage is also an important break point, distinguishing older funds from funds raised after the market peak. In figure 7, we report various absolute and relative performance measures by vintages raised before and after 2004. For unresolved funds, NAV is used as the terminal cash flow. Other cash flows used to calculate returns are net of fees and general partners promotional returns. 

7. Return statistics by class and period

We find that average value-added internal rate of returns (IRRs) for vintages prior to 2004 were in the ballpark of target returns portrayed in figure 1 – especially since the former is net of fees. Although opportunistic IRRs appear lower on average, the variation was great enough that we cannot discern a statistical difference between the average value-added and opportunistic IRRs over the period. For both classes, top quartile returns are greater than 15%.

For vintages between 2004 and 2008, IRRs were unsurprisingly negative on average and statistically smaller than the average from earlier vintages. To be clear, many of the later funds are still unresolved and so reported performance is based to a greater extent on ending NAVs as compared to earlier funds. 

We also make comparisons on the basis of equity multiples, measured as the total value of distributions to limited partners (LPs) – including ending NAV when funds are unresolved – relative to paid-in capital. For pre-2004 vintages, the value-added average multiple was statistically larger than the average opportunistic multiple: 1.7x versus 1.5x. Multiples for top quartile value-added funds approached 2x. On average, funds raised between 2004 and 2008 have not quite returned contributed capital to their LPs. As a testament to the variation in performance across funds, top quartile funds from this period had multiples in excess of 1.25x, whereas the bottom quartile funds have failed to return 30% or more of invested capital. 

As absolute measures of return, IRR and multiples fail to account for the underlying real estate cycle. To evaluate differences in performance between fund classes, we also want to judge how funds in each class performed relative to overall trends in real estate markets. More precisely, we want to assess whether funds did better or worse than similar investments in real estate during a particular period. Making this type of comparison for any sort of private equity investment is challenging. Because private equity funds invest over a four-to-five-year period and harvest investments at irregular times, we often are unable to observe a truly comparable investment. 

Investors in other private-equity sectors rely on a metric called the public market equivalent (PME) measure to help make this type of comparison. It solves the observability problem by calculating returns from making similarly-timed investments in a publicly-traded index. Thus, PME gauges whether a PE investor would have been better or worse off by making the same pattern of investments and withdrawals in a comparable benchmark index. 

For our sample, we report a variant of the PME in which we divide the future value of all fund distributions (compounded at an index rate of return) to the future value of all drawdowns using the same index. A PME greater than one implies that the private investment returns exceeded the returns of the benchmark index. Conversely, a PME less than one implies worse performance. 

A challenge in translating PMEs to real estate hinges on the choice of an appropriate index. Although not publicly-traded, the returns to the ‘NCREIF Fund Index – Open End Diversified Core Equity (ODCE)’ can be obtained net of fees. And while the ODCE index is heavily focused on North American properties, it represents net returns to core real estate assets that may serve as a reasonable baseline against which to compare (presumably) riskier and less liquid private investments. We dub our measure the ‘alternative market equivalent’ or AME since the ODCE index is not publicly-traded. 

Referring again to figure 7, we see that, on a relative basis, the pre-2004 vintages of funds had average returns in excess of returns to the ODCE index. The bottom quartile of value-added funds underperformed the ODCE by 7%, and opportunistic funds underperformed by 14%. The top quartile funds exceeded ODCE returns by 24% or more. 

While returns from funds in vintages 2004 through 2008 were poor in an absolute sense, they also underperformed relative to the ODCE index. Both average and median AMEs for these vintages were around 0.85. In other words, the 2004-08 vintages underperformed core funds in the ODCE index by 15%. For both vintage groups, the AME for value-added and opportunistic funds were statistically indistinguishable. 

Despite our findings in the previous section regarding differences between value-added and opportunistic funds, we find little difference in absolute or relative performance between the two classes. Consistent with strategies that take on greater risk relative to core, value-added and opportunistic funds outperformed the ODCE index in a period of rising returns and underperformed the index in vintages raised on the leading edge of the recent recession. 

In calculating AMEs, we have not controlled for potential differences in risk and financial leverage between funds and the ODCE index. The AMEs in figure 7 are based on the assumption that ‘beta’ is equal to one and that the index is appropriately risk-adjusted to match our sample of funds. We have argued, however, that value-added and opportunistic funds undertake riskier strategies and perhaps greater financial leverage than core funds. Figure 8 shows that AMEs fall when we increase (the assumed) beta. Upon making these adjustments, there are only minor shifts in how value-added funds performed relative to opportunistic funds in either time period. When beta is greater than one, average (leveraged) AMEs for value-added and opportunistic funds were effectively the same. 

8. AME vs beta by class and period

To check whether our simple investigation of average performance fails to capture more nuanced issues within the data, we also run regressions of each performance measure against multiple characteristics of the funds. The regressions examine whether there are class differences in performance for average-size funds within the same vintage year. We still do not find any difference between value-added and opportunistic performance in vintages prior to 2004. For vintages since 2004, North American funds had higher IRRs, and value-added fund multiples were higher than those of opportunistic funds, once controlled for fund size. Larger value-added funds performed worse than smaller funds in the same class in later vintages when measured by multiples or AMEs. Overall, our regression results suggest that vintage year and continent are more important measures of performance than class. 

In conclusion, we show that value-added and opportunistic funds differ in terms of size and focus but, nonetheless, fund class has not been a historical differentiator in performance. This finding calls into question the usefulness of class labels and suggests that investors need to investigate specific managers and the details of their intended strategies in order to assess expected risk and returns. Differentiating funds by focusing on product types, development and geography should be a prerequisite for determining the potential contribution of a fund to an investor’s portfolio. Because the classification of funds is rarely based on information about leverage (due to a lack of consistent data), we also believe that obtaining answers about financial leverage will improve investor understanding of fund risk.

This is a version of a white paper by Landmark Partners

Risk Management: Clearly labelled