Analyzing the performance of non-listed real estate funds: an panel data analysis

The rapid growth of non-listed real estate funds over the last several years has contributed towards establishing this sector as a major investment vehicle for gaining exposure to commercial real estate. Academic research has not kept up with this development, however, as there are still only a few published studies on non-listed real estate funds. This paper aims to identify the factors driving the total return over a seven-year period. Influential factors tested in our analysis include the weighted underlying direct property returns in each country and sector as well as fund size, investment style gearing and the distribution yield. Furthermore, we analyze the interaction of non-listed real estate funds with the performance of the overall economy and that of competing asset classes and found that lagged GDP growth and stock market returns as well as contemporaneous government bond rates are significant and positive predictors of annual fund performance.

A meta analysis of real estate fund performance

This paper provides evidence regarding the risk-adjusted performance of 19 UK real estate funds in the UK, over the period 1991-2001. Using Jensen’s alpha the results are generally favourable towards the hypothesis that real estate fund managers showed superior risk-adjusted performance over this period. However, using three widely known parametric statistical procedures to jointly test for timing and selection ability the results are less conclusive. The paper then utilises the meta-analysis technique to further examine the regression results in an attempt to estimate the proportion of variation in results attributable to sampling error. The meta-analysis results reveal strong evidence, across all models, that the variation in findings is real and may not be attributed to sampling error. Thus, the meta-analysis results provide strong evidence that on average the sample of real estate funds analysed in this study delivered significant risk-adjusted performance over this period. The meta-analysis for the three timing and selection models strongly indicating that this out performance of the benchmark resulted from superior selection ability, while the evidence for the ability of real estate fund managers to time the market is at best weak. Thus, we can say that although real estate fund managers are unable to outperform a passive buy and hold strategy through timing, they are able to improve their risk-adjusted performance through selection ability.

Required returns for real estate in UK pension fund portfolios

The position of Real Estate within a multi-asset portfolio has received considerable attention recently. Previous research has concentrated on the percentage holding property would achieve given its risk/return characteristics. Such studies have invariably used Modern Portfolio Theory and these approaches have been criticised for both the quality of the real estate data and problems with the methodology itself. The first problem is now well understood, and the second can be addressed by the use of realistic constraints on asset holdings. This paper takes a different approach. We determine the level of return that Real Estate needs to achieve to justify an allocation within the multi asset portfolio. In order to test the importance of the quality of the data we use historic appraisal based and desmoothed returns to examine the sensitivity of the results. Consideration is also given to the Holding period and the imposition of realistic constraints on the asset holdings in order to model portfolios held by pension fund investors. We conclude, using several benchmark levels of portfolio risk and return, that using appraisal based data the required level of return for Real Estate was less than that achieved over the period 1972-1993. The use of desmoothed series can reverse this result at the highest levels of desmoothing although within a restricted holding period Real Estate offered returns in excess of those required to enter the portfolio and might have a role to play in the multi-asset portfolio.

An analysis of commercial real estate returns: is there a smoothing puzzle?

In this paper we investigate the commonly used autoregressive filter method of adjusting appraisal-based real estate returns to correct for the perceived biases induced in the appraisal process. Since the early work by Geltner (1989), many papers have been written on this topic but remarkably few have considered the relationship between smoothing at the individual property level and the amount of persistence in the aggregate appraised-based index. To investigate this issue in more detail we analyse a sample of individual property level appraisal data from the Investment Property Database (IPD). We find that commonly used unsmoothing estimates overstate the extent of smoothing that takes place at the individual property level. There is also strong support for an ARFIMA representation of appraisal returns.

Capturing UK real estate volitility

Volatility, or the variability of the underlying asset, is one of the key fundamental components of property derivative pricing and in the application of real option models in development analysis. There has been relatively little work on volatility in real terms of its application to property derivatives and the real options analysis. Most research on volatility stems from investment performance (Nathakumaran & Newell (1995), Brown & Matysiak 2000, Booth & Matysiak 2001). Historic standard deviation is often used as a proxy for volatility and there has been a reliance on indices, which are subject to valuation smoothing effects. Transaction prices are considered to be more volatile than the traditional standard deviations of appraisal based indices. This could lead, arguably, to inefficiencies and mis-pricing, particularly if it is also accepted that changes evolve randomly over time and where future volatility and not an ex-post measure is the key (Sing 1998). If history does not repeat, or provides an unreliable measure, then estimating model based (implied) volatility is an alternative approach (Patel & Sing 2000). This paper is the first of two that employ alternative approaches to calculating and capturing volatility in UK real estate for the purposes of applying the measure to derivative pricing and real option models. It draws on a uniquely constructed IPD/Gerald Eve transactions database, containing over 21,000 properties over the period 1983-2005. In this first paper the magnitude of historic amplification associated with asset returns by sector and geographic spread is looked at. In the subsequent paper the focus will be upon model based (implied) volatility.

The impact of country risk on international real estate returns

Commercial real estate investors have well-established methods to assess the risks of a property investment in their home country. However, when the investment decision is overseas another dimension of uncertainty overlays the analysis. This additional dimension, typically called country risk, encompasses the uncertainty of achieving expected financial results solely due to factors relating to the investment’s location in another country. However, very little has been done to examine the effects of country risk on international real estate returns, even though in international investment decisions considerations of country risk dominate asset investment decisions. This study extends the literature on international real estate diversification by empirically estimating the impact of country risk, as measured by Euromoney, on the direct real estate returns of 15 countries over the period 1998-2004, using a pooled regression analysis approach. The results suggest that country risk data may help investor’s in their international real estate decisions since the country risk data shows a significant and consistent impact on real estate return performance.

Judgments, forecasts and decisions: an analysis of fund managers over time

Decision theory is the study of models of judgement involved in, and leading to, deliberate and (usually) rational choice. In real estate investment there are normative models for the allocation of assets. These asset allocation models suggest an optimum allocation between the respective asset classes based on the investors’ judgements of performance and risk. Real estate is selected, as other assets, on the basis of some criteria, e.g. commonly its marginal contribution to the production of a mean variance efficient multi asset portfolio, subject to the investor’s objectives and capital rationing constraints. However, decisions are made relative to current expectations and current business constraints. Whilst a decision maker may believe in the required optimum exposure levels as dictated by an asset allocation model, the final decision may/will be influenced by factors outside the parameters of the mathematical model. This paper discusses investors' perceptions and attitudes toward real estate and highlights the important difference between theoretical exposure levels and pragmatic business considerations. It develops a model to identify “soft” parameters in decision making which will influence the optimal allocation for that asset class. This “soft” information may relate to behavioural issues such as the tendency to mirror competitors; a desire to meet weight of money objectives; a desire to retain the status quo and many other non-financial considerations. The paper aims to establish the place of property in multi asset portfolios in the UK and examine the asset allocation process in practice, with a view to understanding the decision making process and to look at investors’ perceptions based on an historic analysis of market expectation; a comparison with historic data and an analysis of actual performance.

The production and consumption of commercial real estate market forecasts

Whilst the vast majority of the research on property market forecasting has concentrated on statistical methods of forecasting future rents, this report investigates the process of property market forecast production with particular reference to the level and effect of judgemental intervention in this process. Expectations of future investment performance at the levels of individual asset, sector, region, country and asset class are crucial to stock selection and tactical and strategic asset allocation decisions. Given their centrality to investment performance, we focus on the process by which forecasts of rents and yields are generated and expectations formed. A review of the wider literature on forecasting suggests that there are strong grounds to expect that forecast outcomes are not the result of purely mechanical calculations.

Real estate capital flows and transitional economies

reign real estate capital was a major source of financing domestic property market office construction in Central Europe after the fall of the Berlin Wall in 1989. During the 1990s, over 800 office buildings were either newly constructed or refurbished in Budapest, Prague and Warsaw. The primary focus of this analysis is explaining the spatial construction and redevelopment patterns of the post-1989 office buildings in these cities. Secondarily, we analyze the correlation of foreign direct investment flows to annual construction of office buildings. We seek to explain the location of new or refurbished office buildings in the central business district (CBD) or in non-CBD locations in terms of the effect of time, size of property and other variables, and test whether there is a positive correlation relationship of foreign direct investment flows and new office construction or refurbishment. Integrating relevant foreign direct investment (FDI), economic geography and property theories in the research, the authors attempt to bridge existing gaps in the literature.

The consistency of private and public real estate within mixed-asset portfolios

This study considers the consistency of the role of both the private and public real estate markets within a mixed-asset context. While a vast literature has developed that has examined the potential role of both the private and public real estate markets, most studies have largely relied on both single time horizons and single sample periods. This paper builds upon the analysis of Lee and Stevenson (2005) who examined the consistency of REITs in a US capital market portfolio. The current paper extends that by also analyzing the role of the private market. To address the question, the allocation of both the private and traded markets is evaluated over different holding periods varying from 5- to 20-years. In general the results show that optimum mixed-asset portfolios already containing private real estate have little place for public real estate securities, especially in low risk portfolios and for longer investment horizons. Additionally, mixed-asset portfolios with public real estate either see the allocations to REITs diminished or eliminated if private real estate is also considered. The results demonstrate that there is a still a strong case for private real estate in the mixed-asset portfolio on the basis of an increase in risk-adjusted performance, even if the investor is already holding REITs, but that the reverse is not always the case.

The impact of real estate on the terminal wealth of the UK mixed-asset portfolio

The argument for the inclusion of real estate in the mixed-asset portfolio has concentrated on examining its effect in reducing the portfolio risk - the time series standard deviation (TSSD), mainly using ex-post time series data. However, the past as such is not really relevant to the long-term institutional investors, such as the insurance companies and pension funds, who are more concerned the terminal wealth (TW) of their investments and the variability of this wealth, the terminal wealth standard deviation (TWSD), since it is from the TW of their investment portfolio that policyholders and pensioners will derive their benefits. These kinds of investors with particular holding period requirements will be less concerned about the within period volatility of their portfolios and more by the possibility that their portfolio returns will fail to finance their liabilities. This variability in TW will be closely linked to the risk of shortfall in the quantity of assets needed to match the institution’s liabilities. The question remains therefore can real estate enhance the TW of the mixed-asset portfolio and/or reduce the variability of the TW. This paper uses annual data from the United Kingdom (UK) for the period 1972-2001 to test whether real estate is an asset class that not only reduces ex-post portfolio risk but also enhances portfolio TW and/or reduces the variability of TW.