Returns and Information Transmission Dynamics in Public and Private Real Estate Markets

This paper examines U.S. public and private commercial real estate returns at the aggregate level and by the four major property types over the 1994–2012 time period. Returns are carefully adjusted for differences between public and private markets in financial leverage, property type focus and management fees. Unconditionally, we find that passive portfolios of unlevered core real estate investment trusts (REITs) outperformed their private market benchmark by 49 basis points (annualized) over the 1994–2012 sample period. Our baseline vector autoregression results suggest that REIT returns do not embed additional commercial real‐estate‐specific information useful in predicting private market returns. These results strongly suggest that equity REIT returns react to fundamental (latent) asset pricing information more quickly than private market returns given their greater liquidity and price revelation. REITs therefore serve as a fundamental information transmission channel to private market returns when asset pricing variables are omitted.     

Price Signaling and Return Chasing: International Evidence from Maturing REIT Markets

This article examines the liquidity of international real estate securities across 10 markets over the period 1990–2015. We apply and compare results for four different measures of liquidity, and find that while liquidity has increased consistently, wide variations still exist across markets, with the United States and Japan in the lead. Our results also suggest that the introduction of local REIT regimes did not have any pervasive effects on stock liquidity. When we study the relationship between liquidity and returns, we document new and consistent evidence for international return chasing behavior, whose pattern is a function of local market efficiency, listed real estate market maturity and stock ownership dispersion. The introduction of REIT regimes seems to weaken the importance of extra performance over and above general equity returns as investors tend to allocate funds to real estate securities within real estate rather than equity portfolios.     

Correlation Dynamics and Determinants in International Securitized Real Estate Markets

We find the correlation movements among eight developed securitized real estate markets and among their stock markets are quite synchronized over the period from 1995 through 2012. There is a high degree of correlation dependence with many of the realized correlation series subject to regime switching. Moreover, international correlations of public property returns could be significantly explained by five real estate variables that include global real estate securities market volatility, co‐existence of real estate investment trust (REIT) influence, underlying direct real estate return performance differential, real estate securities volatility differential and real estate securities market size differential after controlling for macroeconomic influence and stock market effect. The importance of the control and real estate variables in explaining the return correlations varies across the economies examined.     

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.     

Investor Sentiment,Limits to Arbitrage and Private Market Returns

This article examines the relation between investor sentiment and returns in private markets. Relative to more liquid public markets, private investment markets exhibit significant limits to arbitrage that restrict an investor's ability to counteract mispricing. Using vector autoregressive models, we find a positive and economically significant relation between investor sentiment and subsequent private market returns. We provide further long‐horizon regression evidence suggesting that private commercial real estate markets are susceptible to prolonged periods of sentiment‐induced mispricing as the inability to short‐sell in periods of overvaluation and restricted access to credit in periods of undervaluation prevents arbitrageurs from entering the market.     

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.     

Short Sales and Price Discovery in the Hong Kong Real Estate Market

Indirect real estate (IRE) returns are often shown to lead direct real estate (DRE) returns. Apart from differences in liquidity, transaction costs, and management skills, the DRE market is also less complete than the IRE market—when negative shocks arrive, one can only short IRE (e.g., real estate stocks or REITs), but not DRE. This study investigates if short sales in the IRE market convey any information to the DRE market. Based on high‐frequency (weekly) property price data in Hong Kong from 2000 to 2012, we find that short sales in the IRE market led DRE returns, even after controlling for the lagged IRE returns in a VAR model. This supports an information spillover mechanism in which the DRE market learns private information that is not reflected in IRE returns. The spillover effect, however, weakened after the recent global financial crisis because the increased uncertainty over the credibility of individual firms made short sales more reflective of firm‐specific information than real estate market fundamentals.     

Option Trading and REIT Returns

This article examines the relation between option trading volume and real estate investment trust (REIT) market performance. Specifically, we find that option volume increases are followed by decreases in returns. Furthermore, the portion of option volume that is orthogonal to REIT characteristics drives the observed return predictability relation, thereby suggesting that the return predictability of option trading is (at least partially) attributable to information‐based explanations. Finally, consistent with informed traders favoring option market activities due to short‐sale costs and/or constraints, we find option based return predictability is more evident within REITs than non‐REITs, even though firms within this industry are generally viewed as informationally transparent.     

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.     

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.     

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.     

Heterogeneous Investor Sentiment and Institutional Real Estate Investments

Commercial real estate investors differ in their sentiment due to factors such as market expertise, investment strategies and expectations about future market conditions. Focusing on the office market, we investigate whether investors with a multiasset investment focus such as pension funds or insurance companies rely on the sentiment of specialized real estate investors such as public REITs or private developers/owners as source of information in their investment decision‐making. Using disaggregated sentiment measures and vector autoregression (VAR) we find evidence that changes in REIT and private real estate investor sentiment lead to changes in institutional investor sentiment in the suburban office and office REIT market. Our findings suggest that institutional investors rely on the sentiment of specialized real estate investors to make real estate investment decisions. Our study contributes to the existing literature on sentiment in commercial real estate markets by emphasizing the heterogeneity of investor sentiment and introducing a disaggregated sentiment measure. We also contribute to the institutional herding literature.     

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.     

Uncertainty premia in REIT returns

We provide a systematic study of how financial and real estate uncertainty affect the aggregate return performance of the U.S. REIT market from 1994 to 2017. A temporal causality analysis reveals a negative uncertainty impact on REIT returns. The asset pricing analysis confirms the predictive relation and suggests that REITs are statistically significantly exposed to changes in market-wide uncertainty, for which investors require a return compensation. We also identify economic state variables to explain time-varying uncertainty exposures as well as periodic hedging characteristics of REITs. Finally, we find evidence that the source of uncertainty matters for compensating expected REIT returns.     

An Analysis of REIT Security Issuance Decisions

This article tests the ability of traditional capital structure theories to explain the issuance decisions of real estate investment trusts (REITs). For issuances made between 1997 and 2006, we find strong support for the market timing theory of capital structure. Controlling for past returns and growth, a REIT is more likely to issue equity when its price-to–net asset value ratio is high. This suggests that REITs issue equity in public markets when the cost of equity capital is lower in the public market than in the private market. Consistent with traditional market timing, REITs are more likely to issue equity after experiencing large price increases. We also find some support for REITs following the trade-off theory of capital structure. REITs are less likely to issue debt when proxies for expected bankruptcy costs are high.     

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.     

The Integration of Commercial Real Estate Markets and Stock Markets

This paper tests whether commercial real estate markets (both exchange-traded and non-exchange-traded) are integrated with stock markets using multifactor asset pricing models. The results support the hypothesis that the market for exchange-traded real estate companies, including REITs, is integrated with the market for exchange-traded (non-real-estate) stocks. Moreover, the degree of integration has significantly increased during the 1990s. However, when appraisal-based returns (adjusted for smoothing) are used to construct real estate portfolio returns, the results fail to support the integration hypothesis, although this may reflect the inability of these estimated private market returns to accurately proxy for commercial real estate returns. Interestingly, the growth rate in real per capita consumption is consistently priced in both commercial real estate markets and stock markets, whereas previous studies have found mixed evidence on the role of consumption in explaining ex ante stock returns.     

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     

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.     

Alternative Benchmarks for Evaluating Mutual Fund Performance

While real estate investment trusts (REITs) have experienced very high growth rates over the past 15 years, the growth in mutual funds that invest in REITs has been even more dramatic. REIT mutual fund returns are typically presented relative to the return on a simple value-weighted REIT index. We ask whether including additional factors when benchmarking funds' returns can improve the explanatory power of the models and offer more precise estimates of alpha. We investigate three sets of REIT-based benchmarks, plus an index of returns derived from non-REIT real estate firms, namely homebuilders and real estate operating companies. The REIT-based factors are a set of characteristic factors, a set of property-type factors and a set of statistical factors. Using traditional single-index benchmarks, we find that about 6% of the REIT funds exhibit significant positive performance using traditional significance levels, which is more than twice what random chance would predict. However, with the multiple-index benchmarks that we prefer, this falls considerably to only 0.7%. In addition, we find that these sets of factors and the non-REIT indices better explain the month-to-month returns of the REIT mutual funds. This suggests that investors or researchers evaluating REIT mutual fund performance may benefit from a multiple-benchmark approach.