Commercial Real Estate Returns

In the commercial real estate market, which is perceived to be relatively inefficient, investors have comparative advantages; hence there are significant costs to diversification. This paper presents for the first time a series of market (or quasi-market) returns for a large data base. This data base is believed to be the most complete commercial real estate data base yet constructed. The paper empirically evaluates the benefits of diversification along various dimensions within the commercial real estate opportunity set. The analysis confirms certain aspects of prior work concerning inflation protection and diversification opportunities while concluding that even investment grade real estate investments are heterogeneous assets.     

Commercial Real Estate Returns: An Anatomy of Smoothing in Asset and Index Returns

In this article, 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. Many articles have been written on appraisal smoothing but remarkably few have considered the relationship between smoothing at the individual property level and the amount of persistence in the aggregate appraisal‐based index. To investigate this issue we analyze a large sample of appraisal data at the individual property level from the Investment Property Databank. We find that commonly used unsmoothing estimates at the index level 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 at the index level and an ARMA model at the individual property level.     

Transactions-Driven Commercial Real Estate Returns: The Panacea to Asset Allocation Models?

A transactions-driven commercial real estate return series is generated in this study to determine whether the reliance on appraised values in the estimation of real estate returns is the source of the reported underpricing of real estate relative to stocks, bonds, and bills when analyzed in a traditional mean-variance setting. The reported underpricing of commercial real estate would be rational if transactions-driven returns exhibit more variance than appraisal-driven returns. While we find that transactions-driven real estate returns have greater variance than appraisal-driven returns for individual properties, most of the individual property risk is idiosyncratic and diversified away at the portfolio level. Real estate continues to be a dominate asset class in mean-variance allocation models even when represented with transactions-driven indices.¹     

A Different Look at Commercial Real Estate Returns

Commercial real estate makes up a relatively small percentage of most institutional portfolios, even though the existing literature has consistently reported attractive risk-return characteristics that would suggest much larger allocations. This discrepancy has been explained by a perceived lack of comparability between return series calculated for real estate and those calculated for other asset classes. Just as investors actively involved in the futures markets do not consider individual common stocks to be traded continuously, those active in the stock market do not consider real estate to be traded continuously. In both cases, adjustments to reported returns are necessary to achieve a degree of comparability. This study makes such adjustments, using sales data from properties that help comprise the National Council of Real Estate Investment Fiduciaries / Frank Russell Company (NCREIF/FRC) Index to generate a "transaction-driven" commercial real estate return series. Examination of the risk-return characteristics of this series shows that it is quite different from traditionally reported real estate return series and far more consistent with risk-return characteristics that have been reported for other asset classes.     

Real Estate Returns and Inflation

The ability of assets to protect an investor from purchasing power risk due to inflation has received a good deal of attention in the literature recently. The focus of much of this research has been on the properties of common stocks as inflation hedges. Bodie [1976] finds that the real return on equity is negatively related to both anticipated and unanticipated inflation; a similar result is obtained by Fama and Schwert [1977] . Bernard and Frecka [1983] examine individual common stock returns and find that the majority exhibit this negative relationship. This paper uses similar logic to examine the ability of a well-diversified portfolio of real estate to hedge against anticipated and unanticipated inflation.     

REIT and Commercial Real Estate Returns: A Postmortem of the Financial Crisis

In the years surrounding the financial crisis, the share prices of equity Real Estate Investment Trusts (REITs) were much more volatile than the underlying commercial real estate prices. To better understand this phenomenon we examine the cross‐sectional dispersion of REIT returns during this time period with a particular focus on the influence of their capital structures. By looking at both the debt ratio and the maturity structure of the debt, we separate the pure leverage effect from the effect of financial distress. Consistent with leverage and financial distress costs amplifying the price decline, we find that the share prices of REITs with higher debt‐to‐asset ratios and shorter maturity debt fell more during the 2007 to early‐2009 crisis period. Although REIT prices rebounded with the bounce back in commercial real estate prices, financial distress costs had a permanent effect on REIT values. In particular, we find that REITs with more debt due during the crisis period tended to sell more property and issue more equity in 2009, when prices were depressed.     

The Motivation for Institutional Real Estate Sales and Implications for Asset Class Returns

Since real estate assets are sold infrequently, analyses that use samples of exclusively sold properties to estimate pricing models may be seriously in error. This paper uses data on samples of sold and unsold properties and an appropriate statistical methodology to evaluate the extent of this bias. The results clearly show that it is important to control for sales motivations and that pricing equations that ignore this source of bias may be misleading.     

Unsmoothing Real Estate Returns: A Regime‐Switching Approach

We propose newly developed unsmoothing techniques for appraisal‐based real estate returns based on a regime‐switching threshold autoregressive (TAR) model. We show that when true returns follow a TAR process, conventional linear autoregressive techniques are misspecified and underestimate true variance. Two exogenous variables, equity returns and gross domestic product growth, outperform other variables as regime indicators and appear to capture risks of downturns in real estate. We extend the model to the smoothing equation, allowing for switching behavior by appraisers, using two new techniques: the TAR‐AR and TAR‐TAR approaches. The “co‐switching” specification opens up a new frontier of empirical research. We estimate the TAR‐TAR using FT returns as the regime indicator, and we find results that outperform conventional smoothing models and have plausible economic explanations.     

Market Microstructure and Real Estate Returns

This paper examines the Real Estate Investment Trust (REIT) market microstruc-ture and its relationship to stock returns. When compared with the general stock market, REIT stocks tend to have a lower level of institutional investor participation and are followed by fewer security analysts. In addition, REIT stocks that have a higher percentage of institutional investors or are followed by more security analysts tend to perform better than other REIT stocks. Our results seem to confirm Jensen's ( 1993 , p. 868) proposition that ownership structure (that is, who owns the firm's securities) affects the value of the firm. Our findings also have implications about the well documented phenomenon that the financial performance of Commingled Real Estate Funds (CREFs) is better than that of REITs.     

Estimating Returns on Commercial Real Estate: A New Methodology Using Latent-Variable Models

Despite their widespreao use as benchmarks of U.S. commercial real estate returns, indexes produced by the National Council of Real Estate Investment Fiduciaries (NCREIF) are subject to measurement problems that severely impair their ability to capture the true risk–return characteristics–especially volatility–of privately held commercial real estate. We utilize latent-variable statistical methods to estimate an alternative index of privately held (unsecuritized) commercial real estate returns. Latent-variable methods have been extensively applied in the behavioral sciences and, more recently, in finance and economics. Unlike factor analysis or other unconditional statistical approaches, latent variable models allow us to extract interpretable common information about unobserved private real estate returns using the information contained in various competing measures of returns that are measured with error. We find that our latent-variable real estate return series is approximately twice as volatile as the aggregate NCREIF total return index, but less than half as volatile as the NAREIT equity index. Overall, our results strongly support the use of latent-variable statistical models in the construction of return series for commercial real estate.     

Historic Returns and Institutional Real Estate Portfolios

This study employs a sample of equity REIT portfolios from 1972–78 to investigate various aspects of real estate returns. Return estimates are derived for the unlevered cash yields by property size, type and location. Based on these data, the effects of certain kinds of diversification on risk-adjusted returns are examined. Finally, historic REIT portfolios are compared to current commingled fund portfolios and suggestions made concerning the benefits of restructuring.     

Real Estate Investments,Product Market Competition and Stock Returns

By limiting operating flexibility, real estate investments are found to increase firm risk, thus expected returns. This study introduces product market competition as a critical determinant of the relation between real estate investments and stock returns. As part of capacity strategies, these investments are generally associated with increased market power and lower cash flow volatility in oligopolistic industries. I present a simple model of oligopolistic competition showing a negative relation between real estate holdings and firm beta, and empirically confirm this prediction. Controlling for product market competition enhances identification of the endogenous relation between real estate investments and stock returns.     

Real Estate in a Mixed‐Asset Portfolio: The Role of the Investment Horizon

In this article, three oft‐mentioned special characteristics of the real estate asset market—high transaction costs, marketing period risk and return predictability—are addressed in analyzing the role of U.K. commercial real estate investments in a mixed‐asset portfolio. Due to favorable horizon effects in risk and return, the allocation to real estate in a portfolio with stocks, bonds and cash increases strongly with the investment horizon. Examining the relative importance of return predictability, transaction costs and marketing period risk for the optimal allocation to real estate, the article finds that the consideration of return predictability is very important, except for short‐term horizons. Accounting for transaction costs is crucial for short‐ and medium‐term investors. Marketing period risk appears to be negligible. Traditional mean‐variance analysis—that is, ignoring return predictability, transaction costs and marketing period risk—can be very misleading.     

Global Financial Integration and Real Estate Security Returns

Have globalization and increasing economic and financial integration affected the rates of return of publicly traded real estate companies around the world? Using a set of multifactor models for annual data for 946 firms from 16 countries over the sample period, 1995–2002, we estimate the impact of a country's economic openness on returns of publicly traded real estate firms, controlling for the effects of global capital markets, domestic macroeconomic conditions and firm‐specific variables. We find that a country's real estate security excess (risk‐adjusted) returns are negatively related to its openness. The results are robust across different multifactor model specifications and are a testament to increasing global financial integration and its interplay with the real estate sector.     

Real Estate Returns and Risk with Heterogeneous Investors

This article develops a theoretical framework and formulates a unified risk metric that integrates both real estate price risk and uncertainty of time on market (TOM). We demonstrate that real estate sellers with different degrees of financial distress face not only different marketing period risks, but also receive different return distributions upon successful sales. The major findings of this article can be summarized as follows. First, we show that real estate return and risk, which account for both price and TOM risk, are investor specific, varying over investors with different financial circumstances and holding periods. Second, the traditional valuation of real estate return and risk, which is based solely on the return distribution of a successful sale without considering the uncertainty of TOM and the investor's financial circumstances, underestimates real estate risk and exaggerates real estate return. Third, our empirical applications in both residential and commercial real estate markets show that the Sharpe ratio estimated by the traditional approach is seriously overstated—to the largest extent for investors with high financial distress. In addition, we find that, given the typical 5‐ to 7‐year holding period for real estate, the Sharpe ratios estimated by integrating both price and TOM risk are much in line with the performance of financial assets. These findings can help to explain the apparent “risk‐premium puzzle” in real estate.     

Timing and the Holding Periods of Institutional Real Estate

Literature on investors' holding periods for securities suggests that high transaction costs are associated with longer holding periods. Return volatility, by contrast, is associated with shorter holding periods. In real estate, high transaction costs and illiquidity imply longer holding periods. Research on depreciation and obsolescence suggests that there might be an optimal holding period. Sales rates and holding periods for U.K. institutional real estate are analyzed, using a proportional hazards model, over an 18-year period. The results show longer holding periods than those claimed by investors, with marked differences by type of property and over time. The results shed light on investor behavior.     

International Real Estate Returns: A Multifactor, Multicountry Approach

We examine the risk and return characteristics of publicly traded real estate companies from 14 countries over the period 1990 to 2001. Our data are monthly country-level commercial real estate indexes constructed by the European Public Real Estate Association (EPRA). We find substantial variation in mean real estate returns and standard deviations across countries. Using various global- and country-level factor models, we find that there is evidence of a strong global market risk component, measured relative to the Morgan Stanley Capital International world index, in most countries. However, even after controlling for the effects of global market risk, an orthogonalized country-specific market risk factor is highly significant, especially for real estate indexes in Asia–Pacific markets. We find that a country-specific value risk factor has some explanatory power in addition to the country-specific market factor, but U.S.-based market, value and size risk factors do not provide any additional explanatory power. These findings imply that the international diversification opportunities with real estate companies are more complex than previously thought.     

Capital Asset Pricing and Real Estate Valuation*

This paper examines the Capital Asset Pricing Model with respect to its implications for real estate investment analysis and appraisal. The derivation of the CAPM, and theoretical problems with it, are discussed, along with its empirical validation. The similarities and differences between real estate and securities markets are evaluated. Alternative models to the CAPM are presented, followed by the conclusions.     

The Cross-Sectional Dispersion of Commercial Real Estate Returns and Rent Growth: Time Variation and Economic Fluctuations

We estimate the cross-sectional dispersions of returns and growth in rents for commercial real estate using data on U.S. metropolitan areas over the sample period 1986 to 2002. The cross-sectional dispersion of returns is a measure of the risk faced by commercial real estate investors. We document that, for apartments, offices, industrial and retail properties, the cross-sectional dispersions are time varying. Interestingly, their time-series fluctuations can be explained by macroeconomic variables such as the term and credit spreads, inflation and the short rate of interest. The cross-sectional dispersions also exhibit an asymmetrically larger response to negative economics shocks, which may be attributable to credit channel effects impacting the availability of external debt financing to commercial real estate investments. Finally, we find a statistically reliable positive relation between commercial real estate returns and their cross-sectional dispersion, suggesting that idiosyncratic fluctuations are priced in the commercial real estate market.     

Asset Allocation and the Performance of Real Estate Mutual Funds

We examine the performance of real estate mutual funds during January 1991–December 1997. As a group, the sampled funds outperformed the Wilshire Real Estate Securities Index on a risk-adjusted basis by more than 5 percentage points annually. We attempt to explain these surprising findings by examining the fund's asset allocations across stocks, bonds and real estate property types using Sharpe's (1992) effective-mix test. We find that all of the superior performance is attributable to fund managers' decisions to overweight outperforming property types (apartments and health care) relative to the Wilshire Real Estate Securities Index weights. Performance of the funds matches a multiple-property-type benchmark that takes account of the fund's exposure to each property type. Therefore, real estate funds demonstrated superior allocation across property types, but neither superior nor inferior selection within property type, during 1991–1997. Our findings emphasize the importance of asset allocation for real estate mutual-fund performance.