Risk management and the corporate real estate portfolio

In a global business economy, firms have a broad range of corporate real estate needs. During the past decade, multiple strategies and tactics have emerged in the corporate real estate community for meeting those needs. We propose here a framework for analysing and prioritising the various types of risk inherent in corporate real estate decisions. From a business strategy perspective, corporate real estate must serve needs beyond the simple one of shelter for the workforce and production process. Certain uses are strategic in that they allow access to externalities, embody the business strategy, or provide entrée to new markets. Other uses may be tactical, in that they arise from business activities of relatively short duration or provide an opportunity to pre-empt competitors. Still other corporate real estate uses can be considered “core” to the existence of the business enterprise. These might be special use properties or may be generic buildings that have become embodiments of the organisation’s culture. We argue that a multi-dimensional matrix approach organised around three broad themes and nine sub-categories allow the decision-maker to organise and evaluate choices with an acceptable degree of rigor and thoroughness. The three broad themes are Use (divided into Core, Cyclical or Casual) – Asset Type (which can be Strategic, Specialty or Generic) and Market Environment (which ranges from Mature Domestic to Emerging Economy). Proper understanding of each of these groupings brings critical variables to the fore and allows for efficient resource allocation and enhanced risk management.

Correlation shifts and real estate portfolio management

The success of any diversification strategy depends upon the quality of the estimated correlation between assets. It is well known, however, that there is a tendency for the average correlation among assets to increase when the market falls and vice-versa. Thus, assuming that the correlation between assets is a constant over time seems unrealistic. Nonetheless, these changes in the correlation structure as a consequence of changes in the market’s return suggests that correlation shifts can be modelled as a function of the market return. This is the idea behind the model of Spurgin et al (2000), which models the beta or systematic risk, of the asset as a function of the returns in the market. This is an approach that offers particular attractions to fund managers as it suggest ways by which they can adjust their portfolios to benefit from changes in overall market conditions. In this paper the Spurgin et al (2000) model is applied to 31 real estate market segments in the UK using monthly data over the period 1987:1 to 2000:12. The results show that a number of market segments display significant negative correlation shifts, while others show significantly positive correlation shifts. Using this information fund managers can make strategic and tactical portfolio allocation decisions based on expectations of market volatility alone and so help them achieve greater portfolio performance overall and especially during different phases of the real estate cycle.

Time weighted portfolio optimisation

In estimating the inputs into the Modern Portfolio Theory (MPT) portfolio optimisation problem, it is usual to use equal weighted historic data. Equal weighting of the data, however, does not take account of the current state of the market. Consequently this approach is unlikely to perform well in any subsequent period as the data is still reflecting market conditions that are no longer valid. The need for some return-weighting scheme that gives greater weight to the most recent data would seem desirable. Therefore, this study uses returns data which are weighted to give greater weight to the most recent observations to see if such a weighting scheme can offer improved ex-ante performance over that based on un-weighted data.

Real estate portfolio construction and estimation risk

The use of MPT in the construction real estate portfolios has two serious limitations when used in an ex-ante framework: (1) the intertemporal instability of the portfolio weights and (2) the sharp deterioration in performance of the optimal portfolios outside the sample period used to estimate asset mean returns. Both problems can be traced to wide fluctuations in sample means Jorion (1985). Thus the use of a procedure that ignores the estimation risk due to the uncertain in mean returns is likely to produce sub-optimal results in subsequent periods. This suggests that the consideration of the issue of estimation risk is crucial in the use of MPT in developing a successful real estate portfolio strategy. Therefore, following Eun & Resnick (1988), this study extends previous ex-ante based studies by evaluating optimal portfolio allocations in subsequent test periods by using methods that have been proposed to reduce the effect of measurement error on optimal portfolio allocations.

The case for property in the long run: a cointegration test

The benefits of property in the mixed asset portfolio has been the subject of a number of studies both in the UK and around the world. The traditional way of investigating this issue is to use MPT with the results suggesting that Property should play a significant role in the mixed asset portfolio. These results are not without criticism and generally revolve around quality and quantity of the property data series. To overcome these deficiencies this paper uses cointegration methodology which examines the longer term time series behaviour of various asset markets using a very long run desmoothed data series. Using a number of different cointegration tests, both pair-wise and multivariate, the results show, in unambiguous terms, that there is no contemporous cointegration between the major asset classes Property, Equities and Bonds. The implications of which are that Property does indeed have a risk reducing place to play in the long-run strategic mixed-asset portfolio. A result of particular relevance to institutions such as pension funds and life insurance companies who would wish to hold investments for the long-term.

Portfolio size and the reduction of dispersion: the case of the United Kingdom commercial real estate market

This paper investigates the potential benefits and limitations of equal and value-weighted diversification using as the example the UK institutional property market. To achieve this it uses the largest sample (392) of actual property returns that is currently available, over the period 1981 to 1996. To evaluate these issues two approaches are adopted; first, an analysis of the correlations within the sectors and regions and secondly simulations of property portfolios of increasing size constructed both naively and with value-weighting. Using these methods it is shown that the extent of possible risk reduction is limited because of the high positive correlations between assets in any portfolio, even when naively diversified. It is also shown that portfolios exhibit high levels of variability around the average risk, suggesting that previous work seriously understates the number of properties needed to achieve a satisfactory level of diversification. The results have implications for the development and maintenance of a property portfolio because they indicate that the achievable level of risk reduction depends upon the availability of assets, the weighting system used and the investor’s risk tolerance.

Risk reduction and real estate portfolio size

Despite a number of papers that discuss the advantages of increased size on risk levels in real estate portfolios there is remarkably little empirical evidence based on actual portfolios. The objective of this paper is to remedy this deficiency by examining the portfolio risk of a large sample of actual property data over the period 1981 to 1996. The results show that all that can be said is that portfolios of properties of a large size, on the average, tend to have lower risks than small sized portfolios. More importantly portfolios of a few properties can have very high or very low risk.

Is there a place for property in the multi-asset portfolio?

The case for property has typically rested on the application of modern portfolio theory (MPT), in that property has been shown to offer increased diversification benefits within a multi asset portfolio without hurting portfolio returns especially for lower risk portfolios. However this view is based upon the use of historic, usually appraisal based, data for property. Recent research suggests strongly that such data significantly underestimates the risk characteristics of property, because appraisals explicitly or implicitly smooth out much of the real volatility in property returns. This paper examines the portfolio diversification effects of including property in a multi-asset portfolio, using UK appraisal based (smoothed) data and several derived de-smoothed series. Having considered the effects of de-smoothing, we then consider the inclusion of a further low risk asset (cash) in order to investigate further whether property's place in a low risk portfolio is maintained. The conclusions of this study are that the previous supposed benefits of including property have been overstated. Although property may still have a place in a 'balanced' institutional portfolio, the case for property needs to be reassessed and not be based simplistically on the application of MPT.

Performance drivers of UK unlisted property funds

An unlisted property fund is a private investment vehicle which aims to provide direct property total returns and may also employ financial leverage which will accentuate performance. They have become a far more prevalent institutional property investment conduit since the early 2000’s. Investors have been primarily attracted to them due to the ease of executing a property exposure, both domestically and internationally, and for their diversification benefits given the capital intensive nature of constructing a well diversified commercial property investment portfolio. However, despite their greater prominence there has been little academic research conducted on the performance and risks of unlisted property fund investments. This can be attributed to a paucity of available data and limited time series where it exists. In this study we have made use of a unique dataset of institutional UK unlisted non-listed property funds over the period 2003Q4 to 2011Q4, using a panel modelling framework in order to determine the key factors which impact on fund performance. The sample provided a rich set of unlisted property fund factors including market exposures, direct property characteristics and the level of financial leverage employed. The findings from the panel regression analysis show that a small number of variables are able to account for the performance of unlisted property funds. These variables should be considered by investors when assessing the risk and return of these vehicles. The impact of financial leverage upon the performance of these vehicles through the recent global financial crisis and subsequent UK commercial property market downturn was also studied. The findings indicate a significant asymmetric effect of employing debt finance within unlisted property funds.

Aligning asset allocation and real estate investment: some lessons from the last cycle

Asset allocation is concerned with the development of multi--‐asset portfolio strategies that are likely to meet an investor’s objectives based on the interaction of expected returns, risk, correlation and implementation from a range of distinct asset classes or beta sources. Challenges associated with the discipline are often particularly significant in private markets. Specifically, composition differences between the ‘index’ or ‘benchmark’ universe and the investible universe mean that there can often be substantial and meaningful deviations between the investment characteristics implied in asset allocation decisions and those delivered by investment teams. For example, while allocation decisions are often based on relatively low--‐risk diversified real estate ‘equity’ exposure, implementation decisions frequently include exposure to higher risk forms of the asset class as well as investments in debt based instruments. These differences can have a meaningful impact on the contribution of the asset class to the overall portfolio and, therefore, lead to a potential misalignment between asset allocation decisions and implementation. Despite this, the key conclusion from this paper is not that real estate investors should become slaves to a narrowly defined mandate based on IPD / NCREIF or other forms of benchmark replication. The discussion suggests that such an approach would likely lead to the underutilization of real estate in multi--‐asset portfolio strategies. Instead, it is that to achieve asset allocation alignment, real estate exposure should be divided into multiple pools representing distinct forms of the asset class. In addition, the paper suggests that associated investment guidelines and processes should be collaborative and reflect the portfolio wide asset allocation objectives of each pool. Further, where appropriate they should specifically target potential for ‘additional’ beta or, more marginally, ‘alpha’.