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.     

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.     

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.     

Temporal Aggregation in Real Estate Return Indices

Temporal aggregation is defined as the use of spot valuations of properties occuring over an interval of time to impute the spot value of a property or of a real estate value index as of a single point in time. Temporal aggregation may characterize not only appraisal-based indices but also indices based directly on transaction prices, such as the National Real Estate Index (NREI) and regression-based indices such as hedonic or repeat-sales indices. This paper analyzes the effect of temporal aggregation on the smoothing of the time series second moments in the resulting real estate return index. Assuming true spot returns are uncorrelated, temporal aggregation-induced smoothing will cause the empirically observed real estate index to understate the own-variance by one-third and the beta by one-half. This amount of bias in the second moments can have major implications for the real estate share in an optimal portfolio. Thus, empirical-based investment analysis could be led astray by smoothing even if the real estate return index is "transaction-based" rather than "appraisal-based."     

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.     

Controlling for the Impact of Variable Liquidity in Commercial Real Estate Price Indices

Liquidity in private asset markets is notoriously variable over time. Therefore, indices of changes in market value that are based on asset transaction prices will systematically reflect intertemporal differences in the ease of selling a property. We define and develop a concept of "constant-liquidity value" in the context of a model that is characterized by pro-cyclical volume of trading. We then present an econometric model that allows for estimation of both a standard transaction-based price index and a constant-liquidity index. Our application to the NCREIF database reveals that, in the case of institutional commercial real estate investment, constant-liquidity values tend to lead transaction-based and appraisal-based indices in time, and also to display greater volatility and cycle amplitude. The differences can be significant for strategic investment policy viewed from a mean-variance portfolio optimization perspective.     

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.     

Comovement After Joining an Index: Spillovers of Nonfundamental Effects

This study considers the case of two overlapping categories in the context of recent category models. Specifically, we examine whether investor sentiment and market frictions specific to one category can affect the returns on assets belonging to the other category. With recent additions of several real estate investment trusts (REITs) into general stock market indices as a natural experiment, we find support for spillovers of such nonfundamental effects, as evidenced by the increased return correlation between REITs that remain outside the index and the index stocks. Further analysis reveals that market frictions play a greater role than investor sentiment.     

Estimating the Lagging Error in Real Estate Price Indices

Real estate indices based on appraisals or sale prices of properties are known for their slow response to market news. These indices can therefore be represented (in logarithm) as the sum of a latent "true" price index and a lagging error. We show that the latent appreciation return and the lagging error can be jointly estimated in a state–space model, which has two key features. First, it employs exogenous variables known to predict asset returns to predict the latent appreciation return. Second, it incorporates known sources of the lagging error, such as the partial adjustment in observed index to the latent appreciation return and the seasonality in reappraisal quality. We find that, after the estimated lagging errors are removed, the appraisal–based National Council of Real Estate Investment Fiduciaries returns become more informative and hence exhibit (i) greater variance, (ii) weaker auto correlation, (iii) higher correlation with the returns of the securitized real estate and (iv) more timely response to market news.     

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.     

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 Effects of the Real Estate Crisis on Institutional Stock Prices

This article investigates the contagious movement of financial institutions' common stock prices in response to real estate news. The basic hypothesis is that because real estate assets are traded infrequently, the market has incomplete information about their true value. The stock price reaction by banks, thrifts and insurance companies to announcements of poorly performing real estate portfolios is studied. Consistent with the hypothesis, significantly negative reactions obtain, both within and across industries, to these announcements. Reflecting the differential regulatory environment and disclosure policies, insurance companies, in general, react more strongly to adverse real estate news. Also, the price reaction of an individual firm is significantly associated with the level of its real estate exposure.     

Appraisal Smoothing: The Other Side of the Story

Appraisal smoothing has been widely accepted as an important factor to consider when analyzing real estate returns using appraisal-based data. In this paper, we demonstrate that the general applicability of the appraisal-smoothing arguments developed so far in the literature is limited by the assumptions upon which the arguments are based. We further show that the use of appraisal-based data can result in a higher (not lower) variance than that of true returns. Given this, it might be more fruitful to analyze the unique characteristics of real estate markets as possible explanations for the seemingly low variance observed in appraisal-based (or transaction-based) return indexes.     

Asset Price Persistence and Real Estate Market Illiquidity: Evidence from Japanese Land Values

We develop an overlapping generations model of the real estate market in which search frictions and a debt overhang combine to generate price persistence and illiquidity. Illiquidity stems from heterogeneity in agent real estate valuations. The variance of agent valuations determines how quickly prices adjust following a shock to fundamentals. We examine the predictions of the model by studying price depreciation in Japanese land values subsequent to the 1990 stock market crash. Commercial land values fell much more quickly than residential land values. As we would posit that the variance of buyer valuations would be greater for residential real estate than for commercial real estate, this model matches the Japanese experience.     

Do Real Estate Prices and Stock Prices Move Together? An International Analysis

The relationship between stock prices and real estate prices has been the subject of substantial debate in both the academic and practitioner literatures. Existing studies have focused on the time series of stock and real estate returns using data from a single country, such as the U.S. By necessity, these studies examine return and price changes over short intervals, creating a bias when property values are smoothed from year to year. Using data from 17 different countries over 14 years, this paper examines the relation between stock returns and changes in property values and rents. Consistent with other country-specific studies, we find that, with the exception of Japan, the contemporaneous relation between yearly real estate price changes and stock returns is not statistically significant. However, when the data are pooled across countries and when we look at longer measurement intervals, a significant relation between stock returns and both rents and value changes becomes apparent. Real estate prices are also found to be significantly influenced by GDP growth rates and provide a good long-term hedge against inflation but a poor year-to-year hedge.     

The Consequences of REIT Index Membership for Return Patterns

The impact of stock market index membership on Real Estate Investment Trust (REIT) stock returns is unclear. Returns may become more like those of other indexed stocks and less like those of their underlying properties. Taking advantage of the inclusion of REITs in major S&P indexes starting in 2001, we find that shared index membership significantly increases the correlation between REIT returns. However, index membership also enhances the link between REIT returns and the underlying real estate, consistent with improved pricing efficiency.     

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.     

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.     

Real Estate Returns: A Comparison with Other Investments

Real estate returns, measured unleveraged, have been between those of stocks and bonds over 1960–1982. Due to appraisal smoothing and imperfect marketability, one must be careful about directly comparing measured real estate returns with those on other assets. It is likely, however, that low correlations with stocks and bonds make real estate a diversification opportunity for traditional portfolio managers. In addition, the issue of how various assets are priced is addressed. While stocks are priced primarily on market or beta risk, and bonds are priced primarily on interest rate and default risk, the real estate pricing mechanism includes residual risk and non-risk factors such as taxes, marketability costs and information costs.     

Smoothing, Nonsynchronous Appraisal and Cross-Sectional Aggregation in Real Estate Price Indices

In this article three econometric issues related to private-equity return indices, such as real estate indices, are explored (smoothing, nonsynchronous appraisal and cross-sectional aggregation). Under certain assumptions, it is found that index returns based on appraisals follow an ARFIMA(1, d , 1) (autoregressive fractionally integrated moving average) process, where the long memory parameter ( d ) explains the level of smoothing and the AR and MA parameters represent the level of persistence in marketwide fundamentals and the nonsynchronous appraisal, respectively. The empirical results show that: (1) the level of smoothing in appraisal-based real estate indices is far less than assumed in many academic studies (2) there is weak evidence of nonsynchronous appraisal in the UK, IPD (Investment Property Databank) index and (3) marketwide fundamentals are highly persistent for the IPD index returns. On the other hand, there is no evidence of nonsynchronous appraisal or a persistent common factor in the U.S. NCREIF (National Council of Real Estate Investment Fiduciaries) index.