The Other Side of Value: The Effect of Quality on Price and Return in Real Estate

We examine the effect of quality on price and return in real estate. Quality real estate stocks generally trade at higher prices. However, similar to findings in the aggregate stock market (Asness et al. 2013), quality in listed real estate is not fully reflected in price. A long quality, short junk portfolio (QMJ) is found to produce average risk-adjusted returns of 3.6 % per quarter (14.4 % annually). QMJ has a significantly positive coefficient when added as a dependent variable to a 4-factor model explaining U.S. real estate excess returns, including market, size, value and momentum factors, and leads to a small improvement in the overall fit of the model. Further investigation of the components of quality shows that profitability has a consistently positive relationship with real estate excess returns, while higher dividend payout is consistently associated with lower returns, in contrast to findings for conventional firms.     

Are Securitized Real Estate Returns more Predictable than Stock Returns?

This paper examines whether the predictability of securitized real estate returns differs from that of stock returns. It also provides a cross-country comparison of securitized real estate return predictability. In contrast to most of the literature on this issue, the analysis is not based on a multifactor asset pricing framework as such analyses may bias the results. We use a time series approach and thus create a level playing field to compare the predictability of the two asset classes. Forecasts are performed with ARMA and ARMA–EGARCH models and evaluated by comparing the entire empirical distributions of prediction errors, as well as with a trading strategy. The results, based on daily data for the 1990–2007 period, show that securitized real estate returns are generally more predictable than stock returns in countries with mature and well established REIT regimes. ARMA–EGARCH models are found to have portfolio outperformance potential even in the presence of transaction costs, with generally better results for securitized real estate than for stocks.     

The Inflation Hedging Characteristics of US and UK Investments: A Multi-Factor Error Correction Approach

Historic analysis of the inflation hedging properties of stocks has produced anomalous results, with stocks often appearing to offer a perverse hedge. This has been attributed to the impact of real and monetary shocks to the economy, which influence both inflation and asset returns. It has been argued that real estate should provide a better hedge: however, empirical results have been mixed. This paper explores the relationship between commercial real estate returns and economic, fiscal and monetary factors and inflation for US and UK markets. Comparative analysis of general equity and small capitalization stock returns is carried out with inflation divided into expected and unexpected components. The analyses are undertaken using an error correction approach. In the long run, once real and monetary variables are included, asset returns are positively linked to anticipated inflation but not to inflation shocks. Adjustment processes are, however, gradual and not within period. Real estate returns, particularly private market returns, exhibit characteristics that differ from those of stocks.

The Relative Importance of Stock, Bond and Real Estate Factors in Explaining REIT Returns

This paper examines the link between REIT, financial asset and real estate returns, and tests whether it changed subsequent to the “REIT boom” of the early 1990s. The main focus is on answering the question do REIT returns now better reflect the performance of underlying direct (unsecuritized) real estate? We develop and implement a variance decomposition for REIT returns that separates REIT return variability into components directly related to major stock, bond, and real estate-related return indices, as well as idiosyncratic or sector-specific effects. This is applied to aggregate REIT sector (NAREIT) returns as well as returns to size and property-type based REIT portfolios. Our results show that the REIT market went from being driven largely by the same economic factors that drive large cap stocks through the 1970s and 1980s to being more strongly related to both small cap stock and real estate-related factors in the 1990s. There is also a steady increase over time in the proportion of volatility not accounted for by stock, bond or real estate related factors. We also find that small cap REITs are “more like real estate” compared to larger cap REITs, at least over the 1993–1998 period. We argue that this could be a result of the institutionalization of the ownership of larger cap REITs that took place in the 1990s.     

The Variation of Economic Risk Premiums in Real Estate Returns

We examine the predictable components of returns on stocks, bonds, and real estate investment trusts (REITs). We employ a multiple-beta asset pricing model and find that there are varying degrees of predictability among stocks, bonds, and REITs. Furthermore, we find that most of the predictability of returns is associated with the economic variables employed in the asset pricing model. The stock market risk premium is highly important in capturing the predictable variation in stock portfolios, and the bond market risk premiums (term and risk structure of interest rates) are important in capturing the predictable variation in bond portfolios. For REITs, however, both the stock and bond market risk premiums capture the predictable variation in returns. REITs have comparable return predictability to stock portfolios. We conclude that there is an important economic risk premium for REITs that are not captured by traditional multiple-beta asset pricing models.     

Is there a real estate factor premium?

In this paper, we study the variation of expected returns on five different asset portfolios in a multi-factor model. We found the presence of a real estate factor, in addition to both a stock factor and a bond factor in asset pricing. This suggests that mutual fund managers should seriously consider including real estate assets in their portfolios, since one cannot capture the real estate factor premium without having some kind of real estate exposure. Another result is that the market segmentation found in previous studies disappears in a more general model of asset pricing in which we allow for multi-factors other than the market factor to affect asset returns. This implies that real estate assets can be treated just like other assets as far as mean-variance efficient asset allocations are concerned. We also have some preliminary evidence that equity REITs and the Russell-NCREIF index are driven by the same underlying real estate factor.     

On the exclusion of assets from tests of the two-parameter model: A sensitivity analysis

This study investigates the sensitivity of tests of the CAPM to different sets of asset returns. Tests are conducted with market portfolios that include returns for bonds, real estate, and consumer durables in addition to common stocks. Even when stocks represent only 10% of the portfolio's value, inferences about the CAPM are virtually identical to those obtained with a stocks-only portfolio. In contrast, inferences are sensitive to the set of assets used in the tests.     

Are REITs real estate? Evidence from international sector level data

The aim of this study is to examine whether securitized real estate returns reflect direct real estate returns or general stock market returns using international data for the U.S., U.K., and Australia. In contrast to previous research, which has generally relied on overall real estate market indices and neglected the potential long-term dynamics, our econometric evaluation is based on sector level data and caters for both the short-term and long-term dynamics of the assets as well as for the lack of leverage in the direct real estate indices. In addition to the real estate and stock market indices, the analysis includes a number of fundamental variables that are expected to influence real estate and stock returns significantly. We estimate vector error-correction models and investigate the forecast error variance decompositions and impulse responses of the assets. Both the variance decompositions and impulse responses suggest that the long-run REIT market performance is much more closely related to the direct real estate market than to the general stock market. Consequently, REITs and direct real estate should be relatively good substitutes in a long-horizon investment portfolio. The results are of relevance regarding the relationship between public and private markets in general, as the ‘duality’ of the real estate markets offers an opportunity to test whether and how closely securitized asset returns reflect the performance of underlying private assets. The study also includes implications concerning the recent financial crisis.     

Book Assets,Real Estate,and Returns on Common Stock

Since real estate is common to most firms, this study examines whether there is a real estate factor in common stock returns that is not completely captured by existing asset pricing models. The three-factor model of Fama and French (1993), hereafter FF, is extended to incorporate a unique real estate factor. Using his extended-FF model, we examine the returns on 53 industry portfolios of common stocks over the 1972 through 1995 time period. The results indicate that a significant 19 percent of the industries are systematically related to the real estate factor. Most interestingly, we show that the loading of the real estate factor in common stock return is related to the loading of the book-to-market equity factor in these returns. We also construct decile portfolios of common stocks based on historical sensitivities of common stock returns to the real estate factor. The coefficients on the real estate factor vary systematically across the decile portfolios. The results of our analysis suggest that portfolio managers should manage their exposure to real estate.     

Owner-occupied homes,income-producing properties,and REITs as inflation hedges: Empirical findings

New evidence on the correlation patterns of various real estate returns with inflation is presented. Returns on a wide array of real estate, nonresidential as well as residential, are investigated. Stock and bond returns are also analyzed for comparison purposes. Extensive heterogeneity is found in real estate return correlations with inflation. Nonresidential property returns are most strongly positively correlated with inflation, although the appreciation in owner-occupied homes is also positively associated with inflation. However, REIT returns tend to be strongly negatively correlated with inflation. In this respect, they look more like traditional stocks and bonds than any other type of real estate. Finally, new evidence on return correlations with energy prices is also presented. Nonresidential real estate performs best here, too, although no real estate asset fully compensates investors for adverse energy price shocks.     

Real Estate Ownership, Leasing Intensity, and Value: Do Stock Returns Reflect a Firm’s Real Estate Holdings?

Little is known about the effects of real estate ownership and leasing on the stock return characteristics of public firms. In this study, we first examine the sensitivity of retail firm returns to a real estate factor over the period 1998?C2008. The retail industry is chosen because of the significant use of real estate in a typical retail firm??s production function. Consistent with our expectations, retail stocks exhibit positive real estate risk exposure, even after controlling for sensitivity to general market risk as well as other standard risk factors. The second part of our analysis examines whether the intensity of real estate ownership and the use of off-balance operating leases to finance real property holdings are reflected in the market and real estate betas of retail stocks. We find that greater use of off-balance sheet operating leases is associated with higher market betas. In fact, the use of operating leases appears to have a larger impact on sensitivity to market risk than does the use of on-balance sheet debt. Our findings also confirm our hypothesis that real estate intensive firms display significantly greater exposure to a real estate factor. Moreover, our results strongly suggest that investors are fully aware of the risk associated with off-balance sheet operating leases.     

The Anatomy of Public and Private Real Estate Return Premia

Market-wide, stock market specific, and real estate market specific risk – what kind of risk and to which extent drives the returns of listed real estate? Based on a structural asset pricing model calibrated to the empirical data in the U.S., we show that at least two thirds of the risk premium of listed real estate are driven by the same factors as direct real estate. Our results shed new light on the risk-characteristics of listed real estate returns and are of high interest for academics, regulators, and portfolio managers alike.     

Time-varying correlation between stock market returns and real estate returns

Direct investment in commercial or residential real estate is found to provide valuable diversification benefits for Australian investors though this is not so evident for indirect real estate investment vehicles like listed Australian real estate investment trusts (A-REIT). Further, multivariate analysis of Australian real estate and share market quarterly returns, spanning the period from the 3rd quarter 1986 to the 3rd quarter 2009, suggest that the correlation between real estate returns and share market returns is time-varying. Finally, while all of the asset class correlation coefficients increased with the Global Financial Crisis period this broad movement in asset class correlation is not evident in during the Wall Street Crash of 1987.     

An analysis of the impact of timberland, farmland and commercial real estate in the asset allocation decisions of institutional investors

We examine the effects of including timberland, farmland and commercial real estate in a mixed asset portfolio with stocks, government bonds and T-Bills. Using both smoothed and unsmoothed returns (as per Geltner [Geltner, D. (1993). Estimating market values from appraised values without assuming an efficient market. Journal of Real Estate Research, 8, 25-345.]) and both constrained and unconstrained allocation assumptions (as per Eichhorn, Gupta and Stubbs [Eichhorn, D., Gupta, F., & Stubbs, E. (1998). Using constraints to improve the robustness of asset allocation. Journal of Portfolio Management, Spring, 41-48.]), we employ Markowitz portfolio optimization and find widely varying allocation outcomes. However, timberland entered nearly all portfolios, accounting for large percentages in several scenarios, while farmland entered only low-risk portfolios. At lower risk levels, commercial real estate dominates the real estate allocation but as acceptable risk levels rise, timberland supplants commercial real estate as the primary component of the portfolio's real estate allocation.     

The value of control: Evidence from full and partial acquisitions in the real estate industry

We investigate the differential wealth effects of (1) full and partial control acquisitions, (2) nonreal estate, real estate and REIT participants, and (3) single- and multiple-bidder events. We find that target firms earn positive excess returns at the announcement of partial and full acquisitions, but acquisitions that result in control earn larger excess returns than noncontrol acquisitions. An examination of industry differences shows that real estate firms or REITs do not earn higher returns relative to nonreal estate firms. Our analysis of market structure finds that bidders that are not involved in an acquisition program earn greater announcement period returns than prior acquirers. For target firms, we find that those with a single offer earn higher returns than those with subsequent offers. A cross-sectional regression analysis shows that while market structure is important in explaining returns, the main determining factor for target firms is the degree of control sought.     

Bank risk and real estate: An asset pricing perspective

While a number of papers have investigated the time-series behavior ofex post bank stock returns and real estate returns, no study has comprehensively studied the relationship betweenex ante risk premiums on both assetsand the time-varying nature of such premiums in relationship to economic and real estate market conditions. In this study, we investigate how the changing nature of bank risk taking, especially in the real estate market, has affected theex ante pricing of risk in the market for bank stocks. We find that the time variation in bank risk premiums are partly determined by interest rate and real estate market conditions. We also discover that the real estate factor has been important for banks in the 1980s.     

Is U.S. economic policy uncertainty priced in China's A-shares market? Evidence from market,industry, and individual stocks

This paper is motivated by Bali, Brown, and Tang (2017) who find U.S. economic policy uncertainty (EPU) is priced in the cross-section of U.S. stock returns, and uses weekly data from March 2006 to April 2016 to study whether shocks in U.S. EPU also influence prices of China's A-shares from a market, industry, and individual stock perspective. Our methodology relies on an ARMA (1,1) model to extract shocks in the U.S. EPU series and a GARCH (1,1) model to examine how returns of China's A-shares respond to these shocks after controlling for business conditions proxied by term and credit spread in China. Generally, we find that shocks in U.S. EPU significantly and negatively explain returns of Chinese A-shares with a lag of one week. In addition, the market index containing small and growth stocks is more sensitive to shocks in U.S. EPU than the index containing big and value stocks. Furthermore, we find that firms in manufacturing, information technology, and media industries in China are more sensitive to shocks in U.S. EPU, while firms in agriculture and real estate industries respond less to shocks in U.S. EPU. Finally, China's A-shares which decline more in response to shocks in U.S. EPU have higher returns, smaller market capitalization, weaker operating profitability, higher asset growth, and better past year's cumulative returns. Overall, our findings show that investors in the Chinese A-shares market require a premium to hold stocks that are sensitive to shocks in U.S. economic policy uncertainty.     

The Role of Real Estate in an Institutional Investor's Portfolio Revisited

Many papers have recently pointed out that institutional investors allocate only a very small fraction of their portfolio to real estate, much smaller than theory would dictate. This raises the question, are institutional investors underinvested in real estate equities? Or do we simply have the wrong priors? This paper is an attempt to provide some new insights into this asset allocation paradox. The key conclusions of the paper are several: First, unlike other assets, it would appear that real estate, and real estate diversification, pays off at the very time when the benefits are most needed, that is, when consumption growth opportunities are low. Second, real estate returns are predictable. In fact, the amount of predictability in real estate returns appears to be about the same as in stock returns. Third, real estate performs well in an asset-liability framework. Fourth, the chance of experiencing a large loss on real estate over a long horizon is quite small. We also report here that private sector commercial real estate investments represent between 6 and 12 percent of investable wealth in the United States. Thus, it follows (if one believes the capital asset pricing model) that if institutional investors were to invest more in real estate (up to 12 percent of their assets), they should be able to eliminate nonmarket or unique risk. All of this leaves us a bit dumbfounded as to why institutional investors hold only between 2 and 3 percent of their assets in real estate.     

Asset market linkages: Evidence from financial, commodity and real estate assets

We use a general Markov switching model to examine the relationships between returns over three different asset classes: financial assets (US stocks and Treasury bonds), commodities (oil and gold) and real estate assets (US Case-Shiller index). We confirm the existence of two distinct regimes: a “tranquil” regime with periods of economic expansion and a “crisis” regime with periods of economic decline. The tranquil regime is characterized by lower volatility and significantly positive stock returns. During these periods, there is also evidence of a flight from quality - from gold to stocks. By contrast, the crisis regime is characterized by higher volatility and sharply negative stock returns, along with evidence of contagion between stocks, oil and real estate. Furthermore, during these periods, there is strong evidence of a flight to quality - from stocks to Treasury bonds.     

Dynamics of Private and Public Real Estate Markets

Using five assets (T-bills, bonds, stocks, and both public and private real estate), this study investigates how cointegration of capital markets affects the dynamics of public and private real estate markets. The results show that the price indices of the five assets are nonstationary and cointegrated. Some implications for the long-term equilibrium relationship for portfolio diversification, price discovery and prediction are discussed. In a Granger causality framework, error-correction augmented VAR models (VECM) and unrestricted VAR models are compared with respect to the conclusion regarding the interaction between public and private real estate returns. VECM is also shown to improve the prediction of private real estate returns relative to an unrestricted VAR model. These results raise questions about previous research studies regarding the dynamics between public and private real estate returns. It is shown that the long-term equilibrium relationship establishes a feedback between the two real estate markets, but the private market seems to informationally lead the public one. Possible explanations are also explored.