Research suggests real estate investment managers are prone to using gut feeling to override more formal analysis
With interest rates and government bond rates at historically low levels, how should real estate organisations make investment decisions? How should they set the discount rates used to evaluate projects? Are the processes and techniques used in real estate markets consistent with sound financial practice? Is real estate ‘different’ to other assets, leading to rational differences in market practice?
These inter-related questions led the Investment Property Forum to commission Cambridge and Aberdeen universities to study investment practice in the UK and Europe. Our report, An Investigation of Hurdle Rates in the Real Estate Investment Process, raises several issues and questions about decision-making in property markets.
Our findings are based on a review of financial theory and practices in other asset markets; detailed interviews with a wide range of organisations in the UK commercial real estate market (figure 1); an extensive survey of market practice in the UK and in wider Europe; and a series of focus groups to discuss our findings and gain feedback on market practices.
It is clear that market practices differ markedly from the recommendations of corporate finance textbooks. In many instances, this is rational and reflects the specific characteristics of property as an asset and the investment vehicles active in the market. However, we observed a wide range of practice and major differences in the sophistication of approach, raising some concerns about the nature of decision-making in the current economic context.
Financial theory is clear that the ‘correct’ way to evaluate an investment project is via discounted cash flow (DCF) analysis and calculation of the net present value (NPV). The discount rate used for the NPV should be based on a firm’s weighted-average cost of capital (WACC) – reflecting the cost of debt and equity holders’ required returns – and acts as a target or hurdle rate. Projects should only be accepted if they generate a surplus when projected cash flows are discounted at that hurdle rate. Firms using an internal-rate-of-return (IRR) approach (considered to be weaker as a technique than NPV) should reject projects that fail to deliver returns above the hurdle rate.
These rules apply to ‘standard’ core investments. Projects that allow the manager more scope to manipulate or engineer the cash flow in the future – value-add or opportunistic investments, perhaps – generate additional value and theory suggests that a ‘real options approach’ should augment DCF. Similarly, where there are interactions between competitor firms, game theory can provide additional insights. Furthermore, risk should be considered at a portfolio level, not at an individual asset level. What matters is a project’s contribution to overall risk and return. A project that, considered individually, might look unattractive, could have important risk diversification properties.
Survey evidence from the corporate sector and other asset classes indicate that larger firms increasingly conform to this model – although IRR is a more popular approach than NPV. Smaller firms, by contrast, are more likely to use less formal decision metrics, such as payback period or profit on cost in preference to DCF-based rules. There is limited evidence of the application of real options (other than in a small number of sectors, for example oil exploration) or game theory. The limited evidence on real estate investment suggests that more informal approaches are prevalent.
“One point frequently brought up in our research was that data was too poor to justify sophisticated quantitative decision models, particularly in thinly traded, opaque markets. This, too, has validity and represents a substantial market failure, in that it has been a common refrain for decades, with limited improvements”
The evidence from our interviews and surveys presented a very mixed picture of UK real estate investment practice. Many organisations did use DCF models to make investment decisions; however, where this was the case IRR dominated NPV as a decision metric. Many organisations, particularly smaller ones, used less formal metrics to drive their project decisions, with profit on cost and equity multipliers of particular importance. Figure 2 shows the results from the survey (largely confirmed by the interviews) with less than half the firms using NPV as their preferred decision tool. In broad terms, larger organisations (particularly those where real estate formed part of a multi-asset portfolio) adopted more sophisticated and rigorous methods, although this was not a universal rule.
From the interviews and focus groups, we were able to probe the use of investment techniques in more detail, which highlighted stark differences from recommended financial practice emerged.
Few organisations formally based their hurdle or target rates on their WACC. More usually, the target rate reflected a valuation-based view of expected return for the particular property sector/market, based on historic performance or on a ‘risk-free-rate-plus-risk-premium’ basis. Many, however, saw the target rate as externally driven: ‘It’s what our clients demand and our competitors offer’.
Whatever the basis, it was standard practice for the hurdle rate to be micro-adjusted for the particular project or investment under consideration. Specific property, location, tenant and other characteristics were used to adjust the risk premium or discount rate, alongside broader sector and geography factors. It is, of course, necessary to reflect project risk in the discount rate, since the WACC should reflect the risk of the typical or average project.
However, that risk adjustment should reflect systematic risk factors (for the type of investment) and the contribution to overall portfolio risk. Standard real estate practice, however, remains very much dominated by individual project level decisions. We found few organisations that formally considered the portfolio aspects.
There were also significant differences in practice of who controlled the decision-making process and the inputs to any model. It was common for the promoting manager or investment team to ‘own’ the analysis and to be able to amend and vary inputs before models were placed before investment committees. Investment committees also typically had the authority to override formal model-based decision criteria and frequently did so.
“There were also significant differences in practice of who controlled the decision-making process and the inputs to any model. It was common for the promoting manager or investment team to ‘own’ the analysis and to be able to amend and vary inputs before models were placed before investment committees. Investment committees also typically had the authority to override formal model-based decision criteria and frequently did so”
We found very few examples of sophisticated quantitative modelling. Best-in-class models incorporated risk analysis through simulation (Monte Carlo) procedures or formal scenario and sensitivity testing. None of those interviewed or surveyed were actively using real options or value-at-risk (VaR) approaches. There were few examples where portfolio considerations were formally incorporated into the decision process, although it was often argued that these did form part of investment committee discussions and that overall portfolio strategy provided a screening of projects being put forward for consideration. Perhaps more concerning, we found little evidence of a ‘culture of learning’ – back testing of models and decisions to test whether investment decisions had the desired outcome and to identify points of weakness in the evaluation process.
At face value, this presents a somewhat concerning picture, suggesting that the real estate sector lags behind other asset classes in adopting more formal analytic methods. Are there, though, specific characteristics of the market that explain the findings?
Market practice and its consequences
In interviews and focus group discussions, as in many industry gatherings, a common refrain was that ‘property is different’. This needs to be treated with caution (other similar private markets have adopted more sophisticated methods), but there are factors and characteristics that might justify some of the market behaviour.
One important aspect of this is organisational structure. Standard finance models are based around ‘the firm’ – typically, a listed entity with shareholders (with required returns on equity), lenders and bond holders (receiving interest on company debt) and managers undertaking multiple projects and activities to deliver returns to those stakeholders. With this structure, a WACC-based NPV approach to investment decisions is natural and appropriate.
For many real estate organisations, however, this does not hold. For fund managers, equity capital (and debt) is obtained based on promised returns (and a characterisation of risk). Those promised returns become, in effect, the targets and the basis for performance-related fees, particularly for an absolute return fund (relative return funds will need to be mindful of expected returns on the chosen benchmark).
We were told on many occasions that the manager has limited discretion in setting these targets which are driven by client expectations
and by the offers of competitor funds. A manager may believe that an appropriate return for a core fund in the current environment is 4%. However, if competitors are promising (and investors are demanding) 8%, it will be difficult or impossible to close a fund at 4%.
One implication of this is that, if clients and competitors were slow to adjust the returns they are demanding in the light of the changing economic context, fund managers would be forced to engineer higher returns by moving up the risk curve, increasing leverage, shifting from core to value-add projects, seeking new markets and sectors (where they may have less expertise and understanding): a real risk of ‘style drift’. The rapid growth of alternative real estate sectors as an investment focus could perhaps be seen in this light.
Similarly, for smaller funds and organisations, the number of assets held or projects initiated will tend to be relatively low. This means that specific project risk is not being diversified fully, leaving the fund vulnerable to poor performance from an individual asset. This would provide a clearer justification for a project-level focus (thus explaining the micro-adjustment of hurdle rates and risk premia), although this should really focus on downside risk, the risk of loss or below benchmark performance. It would certainly justify detailed project level underwriting. Given that large projects (and capital calls) arrive infrequently and are often funded at asset rather than organisation level, again this might to an extent justify project-specific target rates.
Rationality and future prospects
While real estate characteristics help explain market behaviour, the findings represent a cause for concern. Informal methods are prevalent, we found a number of examples where practices were internally inconsistent or at odds with financial principles and there was a general resistance to quantitative methods, particularly if they constrained or went against market intuition. However, other asset markets with similar characteristics have made the transition to the use of formal modelling approaches to support project-level decisions. What barriers remain in commercial real estate markets?
One point frequently brought up in our research was that data was too poor to justify sophisticated quantitative decision models, particularly in thinly traded, opaque markets. This, too, has validity and represents a substantial market failure, in that it has been a common refrain for decades, with limited improvements. There are many barriers to improving data quality and availability, not least a culture of secrecy, of clinging to privileged information. But there may be hope that ‘big data’ technologies will begin to provide the required inputs for more rigorous modelling.
There remain, though, substantial obstacles in terms of culture and skills. Culturally, the idea that real estate is unique in its characteristics and that only market-feel and intuition can provide true insights is a substantial barrier. Clearly, detailed market knowledge is a vital entrepreneurial skill, but one that can be blended with decision-support models to provide more effective decision making.
Skill shortages should be solvable, too, through recruitment processes. However, detailed probing pointed to a problem here: it tended to be senior decision-makers who did not have the financial tools and, consequently, tended to override models in favour of more intuitive approaches from market experience, which then become embedded as best practice. Given the experience of the severe market cycles and concerns about current market state, that seems a brave assumption. It may be that organisations prepared to adopt more analytic approaches – alongside market-derived experience and knowledge – can gain substantial advantages, with disruptive effects that help remove the barriers to change.
The Investment Property Forum research was conducted by the Cambridge Real Estate Research Centre at the University of Cambridge and the Centre for Real Estate Research at the University of Aberdeen. The full report is available from the IPF.
Colin Lizieri is Grosvenor Professor of Real Estate Finance at the University of Cambridge