Risk and Return in the U.S. Housing Market: A Cross-Sectional Asset-Pricing Approach

This article carries out an asset-pricing analysis of the U.S. metropolitan housing market. We use ZIP code–level housing data to study the cross-sectional role of volatility, price level, stock market risk and idiosyncratic volatility in explaining housing returns. While the related literature tends to focus on the dynamic role of volatility and housing returns within submarkets over time, our risk–return analysis is cross-sectional and covers the national U.S. metropolitan housing market. The study provides a number of important findings on the asset-pricing features of the U.S. housing market. Specifically, we find (i) a positive relation between housing returns and volatility, with returns rising by 2.48% annually for a 10% rise in volatility, (ii) a positive but diminishing price effect on returns and (iii) that stock market risk is priced directionally in the housing market. Our results on the return-volatility-price relation are robust to (i) metropolitan statistical area clustering effects and (ii) differences in socioeconomic characteristics among submarkets related to income, employment rate, managerial employment, owner-occupied housing, gross rent and population density.     

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.     

Price Discovery in American and British Property Markets

This paper examines the securitized (public) and unsecuritized (private) commercial property markets in the United States and the United Kingdom for evidence of price discovery. Appraisal-based returns are corrected for smoothing, without presupposing the true returns to be uncorrelated or unpredictable across time. Real Estate Investment Trusts (REITs) and property company returns are corrected for leverage. We find evidence that price discovery occurs in the securitized market structure in both countries, and that this price information does not fully transmit to the unsecuritized markets for a year or more. In Britain, the unsecuritized market appears to be more closely and immediately linked to the securitized market than is the case in the U.S.     

Liquidity, Return and Order-Flow Linkages Between REITs and the Stock Market

This article represents the first exploration of liquidity and order flow spillovers across New York Stock Exchange stocks and real estate investment trusts (REITs). Impulse response functions and Granger causality tests indicate the existence of persistent liquidity spillovers running from REITs to non-REITs. Specifically, REIT liquidity indicators are forecastable from non-REIT ones, at both daily and monthly horizons. I also provide evidence of a liquidity premium inherent in REIT returns. While REIT prices appear to be set efficiently in that neither REIT nor non-REIT order flows forecast REIT returns, I find that order flows and returns in the stock market negatively forecast REIT order flows. This result is consistent with the notion that real estate markets are viewed as substitute investments for the stock market, which causes down-moves in the stock market to increase money flows to the REIT market.     

The Walkability Premium in Commercial Real Estate Investments

This article examines the effects of walkability on property values and investment returns. Walkability is the degree to which an area within walking distance of a property encourages walking for recreational or functional purposes. We use data from the National Council of Real Estate Investment Fiduciaries and Walk Score to examine the effects of walkability on the market value and investment returns of more than 4,200 office, apartment, retail and industrial properties from 2001 to 2008 in the United States. We found that, all else being equal, the benefits of greater walkability were capitalized into higher office, retail and apartment values. We found no effect on industrial properties. On a 100‐point scale, a 10‐point increase in walkability increased values by 1–9%, depending on property type. We also found that walkability was associated with lower cap rates and higher incomes, suggesting it has been favored in both the capital asset and building space markets. Walkability had no significant effect on historical total investment returns. All walkable property types have the potential to generate returns as good as or better than less walkable properties, as long as they are priced correctly. Developers should be willing to develop more walkable properties as long as any additional cost for more walkable locations and related development expenses do not exhaust the walkability premium.     

Seasonality and cultural influences on four Asian stock markets

We use daily returns to identify seasonality on the Kuala Lumpur Stock Exchange (KLSE), The Stock Exchange, Bombay (SEB), the Stock Exchange of Singapore (SES) and The Stock Exchange of Thailand (SET). On all four, we find strong day-of-the-week effects. Month-of-the-year effects exist on the KLSE and the SES but not on the SET or the BSE. Strong Chinese New Year effects are evident on the SES and the KLSE. The Chinese New Year effect on the SET is among small capitalization stocks. On the KLSE, we also find Islamic New Year and Vesak effects, but no Aidilfitri effect. Only weak holiday effects concerning several Indian lunar holidays are evident on the BSE. In general we find that cultural holidays evidence a stronger effect than state holidays. These results confirm the importance of cultural influences in the pricing of stocks.M. W. L. Chan is Professor of Finance and Business Economics at McMaster University, Canada, Anya Khanthavit Associate Professor of Finance, Thammasat University, Thailand and Hugh Thomas Assistant Professor of Finance, McMaster University, Canada. The authors would like to thank the Association of Deans of Southeast Asian Graduate Schools of Management for the financial support that enabled this research to be undertaken and an anonymous referee for his many insightful and constructive suggestions. Please direct all correspondence to Hugh Thomas, School of Business, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4M4, Canada, tel: (905) 522-6861 ext 23983 or email thomas@mcmaster.ca..     

A Measure of Fundamental Volatility in the Commercial Property Market

The low level of volatility observed in appraisal-based commercial property indices relative to other asset classes has been frequently noted and extensively commented on in the real estate finance literature. However, the volatility of such commercial property indices is only one source of information on the second moment of commercial property returns. The volatility of securitized property returns forms another potential source of information, though there is some uncertainty about how closely the volatility of securitized returns may match the volatility of the underlying asset. Each measure of volatility has a potential source of noise associated with it. This paper proposes a fundamental measure of volatility for the commercial property market by using a stochastic volatility model to filter out the signal in the different sources of volatility information. This allows for different measures of volatility to be decomposed into transitory noise and unobserved fundamental volatility. The suitability of such an approach and the properties of the underlying fundamental volatility series are analyzed using data from the U.K. property market.     

Increasing Convergence Between U.S. and International Securitized Property Markets: Evidence Based on Cointegration Tests

This article examines the degree of interdependence among the securitized property markets of six major countries and the United States. Long-run results indicate that, over a period beginning January 1990 and ending August 2007, the property markets of Australia, Hong Kong, Japan, the United Kingdom and the United States are tied together, implying that from the perspective of the U.S. investor the markets of the Netherlands and France provide the greater diversification benefits. Further, the United States and Japan are found to be the sources of the common trends, suggesting that the two larger property markets lead the five (cointegrated) markets toward the long-run equilibrium relationships.     

Regime Shifts in Asian Equity and Real Estate Markets

This paper applies a new statistical technology for identifying regime shifts to analyze recent data on real estate and equity markets in eight developing Far Eastern countries in the 1992–1998 time period. We find that regime shifts in volatility occur in the summer of 1997; however, most of the regime shifts in returns occur in the spring of 1998. While the clustering of regime breaks does not seem to follow any obvious pattern, the country's exposure to trade and firm leverage are important. An analysis of Granger causality suggests that, in most cases, equity returns cause real estate returns but the converse is not true. We also find two-way causality in volatility, suggesting that a common factor drives volatility in these markets. Finally, we provide evidence that the regime shifts generally imply higher relative risk for real estate securities after the estimated breaks.     

On the Relation between Local Amenities and House Price Dynamics

This study explores the extent to which local amenities are related to house price volatility, returns and risk‐adjusted returns across 238 MSAs. We find strong evidence that high amenity areas experience greater price volatility. In regards to returns, high amenity areas experience greater (lower) real returns in appreciating (depreciating) markets. However, high amenity areas experience little to no abnormal risk‐adjusted returns. Results from the study are robust to an endogenous treatment of amenities and land supply elasticity. Overall, we conclude that the desirability of a metropolitan area is a significant channel through which land values drive house price dynamics.     

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.     

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.     

Spatial Linkages in Returns and Volatilities among U.S. Regional Housing Markets

This article investigates spatial linkages in returns, idiosyncratic risks and volatilities across 19 U.S. regional housing markets. Using Case & Shiller housing price indices from 1995 through 2009, we find that interconnections across markets can be “wider” and “stronger” than would normally be expected. They are “wider” because, in addition to geographic closeness, economic proximity is also an important source of influence; they are “stronger” because of the significant contagion effects during the 2007–2009 subprime and financial crises. The increased comovement and interdependence, especially among more geographically diverse regions with similar economic conditions, may help explain the failure of geographic portfolio diversification strategies.     

Big Data Analysis of Volatility Spillovers of Brands across Social Media and Stock Markets

Volatility is an important metric of financial performance, indicating uncertainty or risk. So, predicting and managing volatility is of interest to both company managers and investors. This study investigates whether volatility in user-generated content (UGC) can spill over to volatility in stock returns and vice versa. Sources for user-generated content include tweets, blog posts, and Google searches. The authors test the presence of these spillover effects by a multivariate GARCH model. Further, the authors use multivariate regressions to reveal which type of company-related events increase volatility in user-generated content.Results for two studies in different markets show significant volatility spillovers between the growth rates of user-generated content and stock returns. Further, specific marketing events drive the volatility in user-generated content. In particular, new product launches significantly increase the volatility in the growth rates of user-generated content, which in turn can spill over to volatility in stock returns. Moreover, the spillover effects differ in sign depending on the valence of the user-generated content in Twitter. The authors discuss the managerial implications.     

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.     

Institutional Capital Flows and Return Dynamics in Private Commercial Real Estate Markets

This article examines the short- and long-run dynamics among institutional capital flows and returns in private real estate markets. At the aggregate U.S. level, we find evidence that lagged institutional flows significantly influence subsequent returns. When disaggregating by property type at the national level, we find that capital flows predict subsequent returns in the apartment and office sectors, but not in the retail and industrial markets. At the metropolitan level, we find that the flows help explain subsequent returns in a limited number of core business statistical areas (CBSAs), although these CBSAs collectively represent about 30% of institutional capital. We find no evidence that institutional returns are predictive of future capital flows at the national or CBSA level, suggesting that institutional investors are not chasing returns.     

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.     

GMM Repeat Sales Price Indices

Illiquid assets are widely spread within the economy but their indices are difficult to measure. This paper proposes a Generalized Method of Moment (GMM) repeat sales regression for estimating illiquid asset price indices. This method has estimators that are arithmetic averages of individual asset returns. This method is able to estimate custom-weighted indices, including equal- and value-weighted indices. It can incorporate hedonic variables to improve estimation accuracy, and it can work with a reweighting technique to mitigate a biased sample problem. Simulations based on artificial markets indicate that the method is more accurate than some alternatives in both efficient and sluggish markets, with and without temporal aggregation. As an application, we use this method to estimate a commercial property price index.     

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.