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.     

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.     

Is There a Risk Premium Puzzle in Real Estate?

This paper is based on my Presidential Address to the American Real Estate and Urban Economics Association delivered at Washington, D.C., in January 2003. The paper asks whether there is a risk premium puzzle in real estate. I examine this question by reporting on an empirical investigation of real estate investors' expectations over the last 15 years. The results suggest that ex ante expected risk premiums on real estate are quite large for their risk, too large to be explained by standard economic models. Further, the results suggest that ex ante expected returns are higher than average realized equity returns over the past 15 years because realized returns have included large unexpected capital losses. The latter conclusion suggests that using historical averages to estimate the risk premium on real estate is misleading.     

A Model of Time‐on‐Market and Real Estate Price Under Sequential Search with Recall

This article develops a model and provides a closed‐form formula to uncover the theoretical relationship between real estate price and time on market (TOM). Our model shows a nonlinear positive price‐TOM relationship, and it identifies three economic factors that affect the impact of TOM on sale price. We demonstrate that conventional metrics for real estate return and risk, which are borrowed in a naïve fashion from finance theory, do not account for marketing period risk and tend to overestimate real estate returns and underestimate real estate risks. Our model provides a simple way to correct such bias. This theory helps to explain the apparent “risk‐premium puzzle” in real estate.     

An Approach to Industrial Real Estate Market Segmentation and Valuation Using the Arbitrage Pricing Paradigm

This paper investigates whether a segmented market exists for industrial real estate with respect to risk and return characteristics. Given the existence of industrial market segmentation, the next issue examined is whether a submarket perspective or an integrated real estate market orientation provides better rate of return estimates for individual industrial properties using an Arbitrage Pricing Theory (APT) framework. The results support the existence of regional markets for industrial real estate. A submarket orientation rather than an integrated perspective is also found more appropriate in predicting returns on industrial real estate.     

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.     

U.S. Office Market Values During the Past Decade: How Distorted Have Appraisals Been?

The leading time series of real estate returns is the Russell-NCREIF (RN) Property Index. The RN series tracks returns, cash flow plus appraised capital gains, for multiple property types. To evaluate the accuracy of the capital-gains component of the office-market return series, this paper constructs two benchmark measures for the present value of projectable office-market cash flows from 1982 to 1991 and compares these with a real value series based on the RN capital-gain component. The RN-based series runs 30% above the highest of the benchmarks throughout the 1986–1989 period. While this overstatement is consistent with the development of a price bubble, failure of the bubble to burst until 1990–1991 is implausible. Real estate experts recognized overvaluation in assessments as early as the spring of 1986.
The RN Office-Market Index was slow to register price declines when the markets first weakened and then overstated the rate of decline once the market began to bottom out. This pattern likely reflects incentives for appraisers to smooth potentially temporary price volatility and for investment managers to maintain appraised values in declining markets. It traces as well as to systematic differences in the character and condition of the properties that lend to trade at different stages of the real estate cycle. These incentives and differences provide reason to believe that other RN indexes were similarly distorted.     

Errors in Variables, Links between Variables and Recovery of Volatility Information in Appraisal-Based Real Estate Return Indexes

The present article proposes a multivariate approach to unsmoothing appraisal-based real estate return indexes to recover the true market volatility information in real estate returns. It scrutinizes the role played by errors in variables, in conjunction with an analysis of other economic activities relevant to real estate returns, to exploit the functional relationship and the mechanism of interactions between real estate returns and these economic activities. Appraisal smoothing can therefore be detected and corrected properly and efficiently, without presuming a weakly efficient real estate market. The approach is then applied to U.K. real estate indexes as empirical examples. The results suggest a reasonable volatility in U.K. real estate investment that is close to reality. It is found that the volatility of the true market return on real estate is 1.5404–1.9282 times that of the return on the appraisal-based indexes, in contrast to figures of 2.4862–5.8720 produced by the fully unsmoothing procedure.     

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 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.     

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.     

The Effect of Alternative Return Measures on Restricted Mixed-Asset Portfolios

A restricted portfolio is constructed which includes NYSE common stocks, corporate bonds, government bonds, small capitalization common stocks, residential real estate and farmland and returns for each of four different tax brackets (0%, 15%, 30%, 45%). Next, three alternative measures of rates of return for residential real estate and farmland are used. Finally, since some researchers believe that standard risk measures (variance and standard deviation) do not capture the total risk in real estate, the risk for the real estate returns is increased five times while the returns are held constant. The twenty–four optimal portfolios (four tax brackets with two measures of risk and three measure of return for residential real estate and farmland) are then derived. These results are then compared and contrasted to each other to ascertain the change in sensitivity of the optimal portfolios due to different tax rates, different rates–of–return estimates and different risk estimates.     

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.     

Determinants of Cross-Sectional Variation in Discount Rates, Growth Rates and Exit Cap Rates

This study investigates the determinants of key input variables in valuers' discounted cash flow models used for estimating market values for offices. Data from 599 valuations in 2000 from Stockholm, Gothenburg and Malmö are used to explain variation in discount rates, expected growth rates in net operating income and exit cap rates. Our ability to explain the relatively wide variation in appraisal assumptions with plausible covariates generates confidence in the appraisal process. This has important implications because most value and returns indices of commercial real estate worldwide are appraisal based.     

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.     

Risk and Return on Real Estate: Evidence from Equity REITs

We analyze monthly returns on an equally weighted index of eighteen to twenty-three equity (real property) real estate investment trusts (REITs) that were traded on major stock exchanges over the 1973–87 period. We employ a multifactor Arbitrage Pricing Model using prespecified macroeconomic factors. We also test whether equity REIT returns are related to changes in the discount on closed-end stock funds, which seems plausible given the closed-end nature of REITs.
Three factors, and the percentage change in the discount on closed-end stock funds, consistently drive equity REIT returns: unexpected inflation and changes in the risk and term structures of interest rates. The impacts of these variables on equity REIT returns is around 60% of the impacts on corporate stock returns generally. As expected, the impacts are greater for more heavily levered REITs than for less levered REITs. Real estate, at least as measured by the return performance of equity REITs, is less risky than stocks generally, but does not offer a superior risk-adjusted return and is not a hedge against unexpected inflation.     

Estimating Real Estate's Systematic Risk from Aggregate Level Appraisal-Based Returns

This paper estimates the systematic risk (or "beta") of unsecuritized investment grade commercial real estate, as represented by the FRC and PRISA indices of institutional real estate holdings. Systematic risk defined with respect to national consumption is compared to systematic risk defined with respect to the stock market. Also, the risk estimates are explicitly adjusted to account for "smoothing" in appraisal-based aggregate level returns data. The systematic risk of these real estate indices appears to be virtually zero with respect to the stock market, even after correcting for smoothing, but substantially positive with respect to national consumption.     

Geographic Portfolio Allocations,Property Selection and Performance Attribution in Public and Private Real Estate Markets

This article examines the effects of geographic portfolio concentrations on the return performance of U.S. public real estate investment trusts versus private commercial real estate over the 1996–2013 time period. Adjusting private market returns for differences in geographic concentrations with public markets, we find that core private market performance falls. Using return performance attribution analysis, we find that the geographic allocation effect constitutes only a small portion of the total return difference between listed and private market returns, whereas individual property selection within geographic locations explains, in part, the documented outperformance of listed versus private real estate market returns.     

Macroeconomic Risk Factors and the Role of Mispriced Credit in the Returns from International Real Estate Securities

We examine the canonical influence of global market, currency and inflation risks on the returns from international real estate securities. In addition, we study how mispricing of credit in the local banking systems is related to the returns from these securities. We analyze a global sample of real estate securities over the period 1999 to 2011 to test our hypotheses. We find support for the anticipated relationships between macroeconomic risk factors and the returns from international real estate securities. Our evidence also supports the expected link between local credit market conditions and the performance of international real estate securities.     

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.