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.

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.

The underlying return generating factors for REIT returns: an application of independent component analysis

Multi-factor approaches to analysis of real estate returns have, since the pioneering work of Chan, Hendershott and Sanders (1990), emphasised a macro-variables approach in preference to the latent factor approach that formed the original basis of the arbitrage pricing theory. With increasing use of high frequency data and trading strategies and with a growing emphasis on the risks of extreme events, the macro-variable procedure has some deficiencies. This paper explores a third way, with the use of an alternative to the standard principal components approach – independent components analysis (ICA). ICA seeks higher moment independence and maximises in relation to a chosen risk parameter. We apply an ICA based on kurtosis maximisation to weekly US REIT data using a kurtosis maximising algorithm. The results show that ICA is successful in capturing the kurtosis characteristics of REIT returns, offering possibilities for the development of risk management strategies that are sensitive to extreme events and tail distributions.

Holding periods and investment performance: analysing UK office returns 1983-2003

Drawing on a unique database of office properties constructed for Gerald Eve by IPD, this paper examines the holding periods of individual office properties sold between 1983 and 2003. It quantifies the holding periods of sold properties and examines the relationship between the holding period and investment performance. Across the range of holding periods, excess returns (performance relative to the market) are evenly distributed. There are as many winners as there are losers. The distribution of excess returns over different holding periods is widely spread with the risk of under-performance greater over short holding periods. Over the longer term, excess performance is confined to a narrow range and individual returns are more likely to perform in line with the market as a whole.

The impact of 9/11 on US REIT returns: fundamental or financial?

Following the attack on the World Trade Center on 9/11 volatility of daily returns of the US stock market rose sharply. This increase in volatility may reflect fundamental changes in the economic determinants of prices such as expected earnings, interest rates, real growth and inflation. Alternatively, the increase in volatility may simply reflect the effects of increased uncertainty in the financial markets. This study therefore sets out to determine if the effects of the attack on the World Trade Center on 9/11 had a fundamental or purely financial impact on US real estate returns. In order to do this we compare pre- and post-9/11 crisis returns for a number of US REIT indexes using an approach suggested by French and Roll (1986), as extended by Tuluca et al (2003). In general we find no evidence that the effects of 9/11 had a fundamental effect on REIT returns. In other words, we find that the effect of the attack on the World Trade Center on 9/11 had only a financial effect on REIT returns and therefore was transitory.

Another look at the relative importance of sectors and regions in determining property returns

This paper re-examines the relative importance of sector and regional effects in determining property returns. Using the largest property database currently available in the world, we decompose the returns on individual properties into a national effect, common to all properties, and a number of sector and regional factors. However, unlike previous studies, we categorise the individual property data into an ever-increasing number of property-types and regions, from a simple 3-by-3 classification, up to a 10 by 63 sector/region classification. In this way we can test the impact that a finer classification has on the sector and regional effects. We confirm the earlier findings of previous studies that sector-specific effects have a greater influence on property returns than regional effects. We also find that the impact of the sector effect is robust across different classifications of sectors and regions. Nonetheless, the more refined sector and regional partitions uncover some interesting sector and regional differences, which were obscured in previous studies. All of which has important implications for property portfolio construction and analysis.

International evidence on the predictability of returns to securitized real estate assets: econometric models versus neural networks

The performance of various statistical models and commonly used financial indicators for forecasting securitised real estate returns are examined for five European countries: the UK, Belgium, the Netherlands, France and Italy. Within a VAR framework, it is demonstrated that the gilt-equity yield ratio is in most cases a better predictor of securitized returns than the term structure or the dividend yield. In particular, investors should consider in their real estate return models the predictability of the gilt-equity yield ratio in Belgium, the Netherlands and France, and the term structure of interest rates in France. Predictions obtained from the VAR and univariate time-series models are compared with the predictions of an artificial neural network model. It is found that, whilst no single model is universally superior across all series, accuracy measures and horizons considered, the neural network model is generally able to offer the most accurate predictions for 1-month horizons. For quarterly and half-yearly forecasts, the random walk with a drift is the most successful for the UK, Belgian and Dutch returns and the neural network for French and Italian returns. Although this study underscores market context and forecast horizon as parameters relevant to the choice of the forecast model, it strongly indicates that analysts should exploit the potential of neural networks and assess more fully their forecast performance against more traditional models.

Serial persistence in individual real estate returns in the UK

Persistence of property returns is a topic of perennial interest to fund managers as it suggests that choosing those properties that will perform well in the future is as simple as looking at those that performed well in the past. Consequently, much effort has been expended to determine if such a rule exists in the real estate market. This paper extends earlier studies in US, Australian, and UK markets in two ways. First, this study applies the same methodology originally used in Young and Graff (1996) making the results directly comparable with those in the US and Australian property markets. Second, this study uses a much longer and larger database covering all commercial property data available from the Investment Property Databank (IPD), for the years 1981 to 2002 for as many as 216,758 individual property returns. While the performance results of this study mimic the US and Australian results of greater persistence in the extreme first and fourth quartiles, they also evidence persistence in the moderate second and third quartiles, a notable departure from previous studies. Likewise patterns across property type, location, time, and holding period are remarkably similar leading to the conjecture that behaviors in the practice of commercial real estate investment management are themselves deeply rooted and persistent and perhaps influenced for good or ill by agency effects

Country, sector and regional factors in European property returns

For those portfolio managers who follow a top-down approach to fund management when they are trying to develop a pan-European investment strategy they need to know which are the most important factors affecting property returns, so as to concentrate their management and research efforts accordingly. In order to examine this issue this paper examines the relative importance of country, sector and regional effects in determining property returns across Europe using the largest database of individual property returns currently available. Using annual data over the period 1996 to 2002 for a sample of over 25,000 properties the results show that the country-specific effects dominate sector-specific factors, which in turn dominate the regional-specific factors. This is true even for different sub-sets of countries and sectors. In other words, real estate returns are mainly determined by local (country specific) conditions and are only mildly affected by general European factors. Thus, for those institutional investors contemplating investment into Europe the first level of analysis must be an examination of the individual countries, followed by the prospects of the property sectors within the country and then an assessment of the differences in expected performance between the main city and the rest of the country.