Privately Versus Publicly Held Asset Investment Performance

Classic asset pricing is problematic as a method to assess privately held asset investment performance. We propose an alternative approach that involves adjusting the characteristics of assets constituting an index or portfolio to match the asset characteristics of a reference index or portfolio. This approach is applied to commercial real estate, where we create an index of REIT returns to compare to the NCREIF index. To enhance comparability, return indices are adjusted for partial-year financial data, leverage, asset mix and fees. Adjusted results over a 1980–1998 sample period show general convergence between the indices, although an annual return difference of over three percentage points remains in favor of public market asset ownership. Possible causes of the investment performance gap include liquidity and geography as missing risk factor adjustments, an unrepresentative sample period, and the form in which commercial real estate assets are held.     

What Does the Stock Market Tell Us About Real Estate Returns?

This paper analyzes the risks and returns of different types of real estate-related firms traded on the New York and American stock exchanges (NYSE and AMEX). We examine the relation between real estate stock portfolio returns and returns on a standard appraisal-based index, and find that lagged values of traded real estate portfolio returns can predict returns on the appraisal-based index after controlling for persistence in the appraisal series. The stock market reflects information about real estate markets that is later imbedded in infrequent property appraisals. Additional analysis suggests that the differences in the return and risk characteristics across different types of traded real estate firms can be explained in part by appealing to real estate market fundamentals relating to the degree of dependence of the real estate firm upon rental cash flows from existing buildings. These findings highlight the heterogeneity of securitized real estate-related firms.     

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     

Real Estate Fund Openings and Cannibalization

This article examines the trade‐offs in launching new real estate funds, specifically open‐end, direct‐property funds. This investment vehicle, which is designed to provide the risk‐return benefits of private market real estate, is available to retail investors in a number of countries. At the same time, these funds are also subject to liquidity risk, because they hold an inherently illiquid asset in an open‐end structure. This format presents fund‐family managers with unique challenges, particularly with the decision to open new funds. The data consist of 2,127 German fund openings across 76 fund families in 12 asset classes over the 1992–2010 period. Including a wide range of asset classes allows for a comparison between real estate and other investment objectives. We find a substantial cannibalization effect across the existing real estate funds of a family, while we note the opposite effect—i.e., flows into existing funds increase following a fund opening within the same objective—for all other asset classes. Our analysis of fund opening determinants shows that inflows mitigate the cannibalization risk for new real estate funds. Additional evidence highlights the role of scale and scope economies in real estate fund openings. Overall, the results provide new insights into the relatively large size and small number of real estate funds when compared to mutual funds dedicated to other investment objectives.     

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.     

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.     

Real Estate in an ALM Framework: The Case of Fair Value Accounting

This study examines the liability hedging characteristics of both direct and indirect real estate with the advent of fair value accounting obligations for pension funds. We explicitly model pension obligations as being subject to interest and inflation risk to analyze the ability of real estate investments in hedging the fair value of pension liabilities and to quantify its role in an asset liability management (ALM) portfolio. We find that the portfolio composition differs depending on the definition of liability return. When liability returns solely follow actuarial changes, the mean‐variance efficient portfolio allocations toward direct real estate and fixed income decrease compared to the asset‐only optimization. When accounting for nominal liability obligations, real estate offers hedging benefits against interest rates for short holding periods but not for long‐term institutional portfolios. The inclusion of inflation risk renders a limited role for direct real estate in an ALM portfolio, while indirect real estate obtains no allocation. Inflation is at the heart of the discrepancy between reported and predicted pension plan allocations. Once accounting for inflation, the projected allocations come close to reported ones.     

Market Efficiency and Return Statistics: Evidence from Real Estate and Stock Markets Using a Present-Value Approach

This paper develops a methodology to identify asset price response to news in the framework of the Campbell–Shiller log-linear present-value equation. We further show that a slow price adjustment in real estate markets not only induces a high serial autocorrelation in excess returns, but also dampens the return volatility and the correlation with excess returns in other asset markets. Using Hong Kong real estate and stock market data, we find that the quarterly real estate price assimilates only about half the effect of market news, whereas the quarterly stock price incorporates the news fully. Our analysis identifies a cumulative price adjustment that recovers lost information in real estate returns due to market inefficiency and thereby restores the real estate return volatility and the correlation between real estate and stock markets.     

Another Take on Real Estate's Role in Mixed‐Asset Portfolio Allocations

This article examines real estate's role in institutional mixed‐asset portfolios using both private‐ and public‐real estate indices, as a means of examining varying real estate‐related risk/return opportunities. In so doing, this article also examines the effects of: (1) increasing the investment horizon, (2) placing constraints on the maximum allocation to any one asset class, and (3) varying the risk preferences of investors. The empirical results suggest—using infinite‐horizon returns and all of the caveats that accompany such a perspective—that real estate allocations of approximately 10–15% of the mixed‐asset portfolio represent an upper bound for most investors. For those investors preferring low‐risk portfolios, (unlevered) private real estate is the vehicle serving this allocation preference; for those investors preferring high‐risk portfolios, public real estate (with its embedded leverage of 40–50%) is the vehicle serving this allocation preference—with such vehicles serving as substitutes for a variety of noncore real estate strategies. In some sense, the distinction between private and public real estate is more about the use of leverage. For those investors preferring moderate‐risk portfolios, an intermediate‐leverage approach seems optimal.     

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.     

Integrating Illiquid Assets into the Portfolio Decision Process

We consider the issues associated with modeling the decision to invest in an illiquid asset, such as real estate, over an extended period of time. Markets for illiquid assets tend to display certain characteristics: for example, significant time‐till‐sale and correlation in the rates of return over time. More importantly, as the liquidity of a market cannot be an issue if an investor never needs to liquidate an asset, we focus on how the liquidity of a market interacts with an individual's uncertain need to liquidate. We show that the optimal strategy is state contingent, if possible. We also show that the penalty associated with an illiquid investment depends on the characteristics of other assets being held in the portfolio, on the characteristics of liquidity shocks and on the interaction between time and behavior. We show that borrowing to pay for a liquidity shock cannot overcome all of the costs of owning an illiquid asset. In contrast, borrowing at t = 0 benefits from the complementarity in the assets. In a simpler model, we show that the portfolio perspective makes illiquid assets more valuable to an investor with a longer time horizon.     

On the Portfolio Properties of Real Estate in Good Times and Bad Times1

Motivated by the theoretical results on strategic asset allocation, we examine the gains in portfolio performance when investors diversify into different asset classes, with particular focus on the timeliness of such gains. Although the various asset classes we analyze yield significant gains in portfolio performance, even in the presence of short‐sales constraints, the timeliness of the gains differs considerably across the asset classes. Our key result is that real estate and commodities and precious metals are the two asset classes that deliver portfolio gains when consumption growth is low and/or volatile, that is, when investors really care for such benefits. Our analysis highlights an important metric by which to judge the attractiveness of an asset class in a portfolio context, namely the timeliness of the gains in portfolio performance. Further, our results on the performance of real estate in both good times and bad times suggest that the typical institutional allocation to real estate may underweight the role of the asset class in a diversified portfolio context.     

Real Estate Investment Funds: Performance and Portfolio Considerations

This paper presents the results of a study dealing with a number of issues regarding real estate investment. Utilizing a data set consisting of returns from two of the oldest, continuously operating commingled real estate funds (CREFs), questions relative to investment performance, inflation hedging attributes and diversification benefits are addressed. The methodology used in exploring these issues are variants of the traditional capital asset pricing model (CAPM), extended to consider uncertain inflation (CAPMUI) and an arbitrage pricing model in which real estate performance is judged relative to a more inclusive market index representing larger numbers of substitute investments. Finally, issues relative to portfolio performance are considered by constructing portfolios containing all possible combinations of real estate, stocks and bonds to assess the potential for diversification benefits and portfolio performance.     

The Fractal Structure of Real Estate Investment Trust Returns: The Search for Evidence of Market Segmentation and Nonlinear Dependency

This article presents a further test for market segmentation between the real estate market and the capital markets. We use rescaled range analysis developed in the fractal geometry literature to test for nonlinear trends in the returns series for different asset classes. We make three major conclusions: (1) the stock market displays tendencies consistent with a random walk, (2) portfolios of mortgage and equity REIT returns display tendencies consistent with a random walk and, (3) conditional upon the methods used, segmentation does not exist between different real estate markets and between the real estate and stock markets.     

Public Versus Private Real Estate Equities: A More Refined, Long-Term Comparison

In this article we compare public and private real estate equities. In so doing, we control for three of the main differences between these investment alternatives: property-type mix, leverage and appraisal smoothing. With these two restated indices, we then run tests to determine in a statistical sense whether the restated means and volatilities of the two series were different from one another. The clear answer is that they were not. The results of the statistical tests combined with the fact that the average difference between the two (restated) return series has substantially narrowed (to approximately 60 basis points) in the more recent (1993–2001) period jointly suggest a seamless real estate market in which public- and private-market vehicles display a long-run synchronicity. This has important implications for portfolio management. First, public- and private-market vehicles ought to be viewed as offering investors a risk/return continuum of real estate investment opportunities. Second, while the "platform" did not matter in terms of observed return characteristics, the platform may matter with regard to liquidity, governance, transparency, control, executive compensation and so forth; an apparent clientele effect hints at these issues being valued differently by large and small investors.     

A Comparative Anatomy of Residential REITs and Private Real Estate Markets: Returns,Risks and Distributional Characteristics

Real Estate Investment Trusts (REITs) are the only truly liquid assets related to residential real estate investments. We study the behavior of U.S. Residential REITs over the past three decades and document their return characteristics. REITs have somewhat less market risk than equity; their betas against a broad market index average about 0.58. Decomposing their covariances into principal components reveals several strong factors. Residential REIT characteristics differ to some extent from those of the S&P/Case‐Shiller (SCS) private real estate markets. This is partly attributable to methods of index construction. Our examination of REITs suggests that investment in residential real estate is far more risky than what might be inferred from the widely followed SCS series. Although the SCS and REITs indicate little support for being able to predict each other, there is strong evidence of self‐predictability for the series.     

Real Estate for the Long Term: The Effect of Return Predictability on Long-Horizon Allocations

We examine how the predictability of real estate returns affects the risk of, and optimal allocations to, real estate for investors of differing investment horizons. Returns to direct real estate are mean reverting, and risk decreases with horizon. This is driven by a tendency for property transaction prices to overshoot inflation. Mean reversion in real estate returns is weaker than that of equities, resulting in real estate having similar risk to equities for long-term investors. However, optimal portfolios have large allocations to direct real estate at all horizons, and the allocation increases with horizon. Finally, we find that real estate investment trusts are a redundant asset class for investors with access to direct real estate as an asset class, but they do have a role in optimal allocations when direct property investment is not feasible.     

Twenty Years of the NCREIF Property Index

This study overviews the performance of the NCREIF Property Index, by property type, over the twenty-year period ended in 1998. More exactly, performance is analyzed from the perspective of the fundamental sources of return: initial earnings yield, dividend payout ratios, earnings growth, shifts in capitalization rates and other (less significant) effects. (While this approach is here applied to private real estate equities, nothing precludes its application to a variety of other investment classes.) Our results indicate the fundamental sources that have contributed to the Index's considerable cross-sectional variation as well as its time-series variation. Therefore, this study should be viewed as a useful historical account for those interested in understanding the ex post return-generating process of the Index and its property-type components as well as those who wish to model the ex ante return-generating process for a variety of applications in both the equity and debt markets—regardless of whether the securities are publicly or privately traded.     

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.     

Illiquidity and Pricing Biases in the Real Estate Market

This article addresses the micro-analytic foundations of illiquidity and price dynamics in the real estate market by integrating modern portfolio theory with models describing the real estate transaction process. Based on the notion that real estate is a heterogeneous good that is traded in decentralized markets and that transactions in these markets are often characterized by costly searches, we argue that the most important aspects defining real estate illiquidity in both residential and commercial markets are the time required for sale and the uncertainty of the marketing period. These aspects provide two sources of bias in the commonly adopted methods of real estate valuation, which are based solely on the prices of sold properties and implicitly assume immediate execution. We demonstrate that estimated returns must be biased upward and risks downward. These biases can be significant, especially when the marketing period is highly uncertain relative to the holding period. We also find that real estate risk is closely related to investors' time horizons, specifically that real estate risk decreases when the holding period increases. These results are consistent with the conventional wisdom that real estate is more favorable to long-term investors than to short-term investors. They also provide a theoretical foundation for the recent econometric literature, which finds evidence of smoothing of real estate returns. Our findings help explain the apparent risk-premium puzzle in real estate—that is, that ex post returns appear too high, given their apparent low volatility—and can lead to the formal derivation of adjustments that can define real estate's proper role in the mixed-asset portfolio.