Real Estate Returns Research Articles

Soft Negotiators or Modest Builders? Why Women Earn Lower Real Estate Returns

Soft Negotiators or Modest Builders? Why Women Earn Lower Real Estate Returns

Heat Stress and Commercial Real Estate Returns

Heat Stress and Commercial Real Estate Returns

Is e-commerce an investment risk priced by retail real estate investors? An investigation

ABSTRACT Over the last 20 years, online shopping has evolved into a major threat to the physical retail store. We investigate whether retail real estate investors price e-commerce as an investment risk. In particular, we analyse whether e-commerce sales have informative value for retail real estate returns. Focusing on institutional-grade shopping centres over the period of 2000 to 2018, we find that e-commerce sales predict total returns in the next quarter. This effect is driven by capital returns, which suggests that e-commerce is indeed priced as an investment risk. While consistent across mall types, this effect is stronger for regional and super-regional malls than neighbourhood and community shopping centres. Explanations for this difference include the types of retail tenants in these different mall categories and the varying impact of e-commerce on their business.

Does investor sentiment differently affect stocks in different sectors? Evidence from China

PurposeThis paper aims to investigate the dynamic relationship between the investor sentiment and the return of various sectors in the Chinese stock market.Design/methodology/approachThe wavelet coherence and wavelet phase angle approaches are used to study the lead–lag associations between sentiment index and stock returns in a time–frequency way. The multiscale linear and nonlinear Granger causality tests are performed to explore whether there is a causality between them.FindingsThe empirical results show that during normal period, investor sentiment index has a stronger relationship with stock returns of industrials, consumer discretionary, health care, utilities, real estate and financial sectors. In crisis period, investor sentiment has a significant positive relationship with all industry sectors. In the short term, there is bidirectional causality between investor sentiment and stock returns of all sectors. In the medium and long run, almost all sector stock returns Granger-cause the investors' sentiment index but investor sentiment does not Granger-cause all sectors, which is in contrast to the developed markets.Practical implicationsThe interindustry impact of investment sentiment on the stock market can help construct arbitrage portfolio by investors who are interested in Chinese stock market.Originality/valueThis paper focuses on the industry sector differences of investor sentiment impact on the Chinese stock market. As far as the authors know, this is the first paper to explore the time–frequency relationship between sentiment index and industry stock returns in China using the time–frequency method based on wavelet coherence, which considers the heterogeneity of different types of investors' responses to various economic and financial events.

Real estate illiquidity and returns: A time-varying regional perspective

This paper proposes two new measures of illiquidity for real estate markets, utilising concepts from asset pricing. Segregating real estate through a regional lens, we provide an in-depth analysis of real estate returns and illiquidity for the US and UK. Our results provide statistically significant and economically meaningful evidence that real estate illiquidity predicts real estate returns out-of-sample over and above a variety of control variables.

Impact of Global Residential Real Estate on Portfolio Diversification

The purpose of this paper is to examine the benefits of international diversification in residential real estate markets during various market conditions from 1999 through 2018. Most previous studies used real estate investment trusts (REITs) indexes to proxy for real estate returns, while our research is focused on residential real estate indexes provided by Dallas Federal Reserve Bank. In addition, we expand our study to 23 countries, while previous research was limited to 5 to 10 countries. We find lower correlation between US stocks and global real estate indexes. Further analysis indicates that adding international real estate to a US stock portfolio is beneficial in reducing portfolio risk, and this diversification benefit is consistent over time. Our results will assist portfolio managers and long-term investors in keeping a consistent return at a lower risk.

Can the Textual Tone in REIT Financial Statements Improve the Information Environment for Commercial Real Estate Investors? An Investigation

The SEC requires publicly traded REITs to discuss commercial real estate market conditions in their financial statements in order to provide REIT investors with decision-relevant information. We investigate whether the textual tone in REIT financial statements (10-K/10-Q) can be used to predict future commercial real estate returns. In our empirical investigation, we focus on forward-looking tone, i.e., tone that cannot be explained by a REIT’s past performance. We extract textual tone from quarterly REIT financial statements over the period from 2002 to 2017 by using both a generic finance dictionary and a new, REIT-specific dictionary. We then employ a regime-switching methodology to assess the informative value of forward-looking tone for commercial real estate returns in the next quarter. We find that in periods of poorly performing real estate markets the forward-looking tone in REIT financial statements predicts total returns in the next quarter. This effect is driven by capital returns and is most pronounced for apartment and retail. Our findings suggest that the tone in REIT financial statements can help improve the information environment for commercial real estate investors.

Value Creation of Real Estate Company Spin-off Property Service Company Listing

Abstract The paper took 12 groups of parent companies and subsidiaries as the samples, in which the property service companies, spun from the real estate companies, have successfully on the capital market. The research showed that the average abnormal return (AAR) of real estate companies’ stocks was positive on the first announcement date of possible spin-off listing, while the cumulative average abnormal return (CAAR) remained positive for 21 days during the (–11, 9) days around the first announcement of possible spin-off and listing. Further, the changes in operating performance of real estate companies and property service companies were analysed after the successful spin-off for 3 consecutive years, compared with the year before the spin-off and listing. The results showed that after the spin-off and listing, real estate companies and property service companies have greatly improved their performance. Therefore, the fact that real estate companies spun off property service companies created positive values for shareholders.

Government responses to COVID-19 and industry stock returns

Governments around the world have responded to the COVID-19 outbreak with a mix of policies. The strictest responses of the New Zealand government are notable, given their abilities to contain and limit the spread of the virus. However, their impacts on stock returns remain unclear. This paper investigates the impact of three policies, namely lockdown, the stimulus package, and the travel ban, on the returns of 14 New Zealand industry stock indices. Using daily data from 1 January 2019 to 25 August 2020, evidence points to a heightened level of integration among the various industry stock indices during the early stages of the pandemic. Only lockdown has had a positive impact on aggregate stock returns, suggesting its ability to raise investors’ confidence in the overall stock market. At the industry level, the impact of the three response policies is generally positive but heterogeneous across industry stock indices. Notably, none of the three adopted policies significantly impact technology, healthcare, and real estate returns.

International Real Estate Review

We apply the dynamic Gordon growth model to the Hong Kong real estate market to analyze quarterly data on four kinds of real estate—housing, office, retail, and factory properties—from 1999 to 2020. We find that factories have the highest total returns among the four types of real estate, and also a larger Sharpe ratio. The total returns of these four kinds of real estate are highly correlated. The results of an autoregressive distributed lag model show that the gross domestic product growth rate is the key determinant of real estate returns, while changes in foreign direct investment also influence housing and retail returns. The expected value of the risk-free rate is the key factor that determines the rent-price ratio. The decline in the risk-free rate in Hong Kong is the main reason that the real estate price-rent ratio has increased from 20 to 40 in the last twenty years. Our research represents an early contribution that compares the performance of housing and commercial real estate at the city level, with both types of real estate having similar determinants. Finally, we find that the fall in risk-free interest rates worsens housing affordability in Hong Kong.

The effect of sentiment on commercial real estate returns: investor and occupier perspectives

PurposeReal estate is an asset that is traded in highly segmented, illiquid and informationally inefficient local markets. A short sale in real estate is almost infeasible and therefore impedes informed rational arbitrageurs to trade against mispricing. Thus, real estate returns are prone to sentiment-driven behaviours. Will the impacts on asset returns be identical for different types of sentiment?Design/methodology/approachThis study argues that not all sentiment effects are created equal. Using the bounds test of the autoregressive distributed lag (ARDL) models, this paper examines how occupier sentiment versus investor sentiment contributes to the short-run and long-run dynamics of commercial real estate returns in Australia.FindingsThe empirical evidence suggests that investor sentiment and occupier sentiment influence return asymmetrically after macroeconomic conditions are controlled for.Practical implicationsThe sectoral analysis further reveals that sector-specific sentiment plays a significant role in explaining commercial real estate returns. Furthermore, notable improvement is found in producing more accurate prediction in returns, given that measures of occupier and investor sentiment are appropriately specified in the forecast.Originality/valueThis study is novel in the sense that it acknowledges the impacts of occupiers' and investors' sentiment may be fundamentally different. The unique innovation and contribution of this study to behavioural finance literature are based on a new dataset from the Royal Institute of Chartered Surveyors which includes a survey-based measure of investor sentiment and occupier sentiment.

Why Women Earn Lower Real Estate Returns

Why Women Earn Lower Real Estate Returns

Residual-augmented IVX predictive regression

Bias correction in predictive regressions is known to reduce the empirical size problems of OLS-based predictability tests with persistent predictors. This paper shows that bias correction is also achieved in the context of the extended instrumental variable (IVX) predictability testing framework introduced by Kostakis et al. (2015). To be specific, new IVX-based statistics subject to a bias correction analogous to that proposed by Amihud and Hurvich (2004) are introduced. Four important contributions are provided: first, we characterize the effects that bias-reduction adjustments have on the asymptotic distributions of the IVX test statistics in a general context allowing for short-run dynamics and heterogeneity; second, we discuss the validity of the procedure when predictors are stationary as well as near-integrated; third, we conduct an exhaustive Monte Carlo analysis to investigate the small in- and out-of-sample properties of the test procedures and their sensitivity to distinctive features that characterize predictive regressions in practice, such as strong persistence, endogeneity, and non-Gaussian innovations; and fourth, we provide an analysis of real estate return and rent growth predictability in 19 OECD countries.

Practical Applications of Real Estate Returns

Practical Applications In Real Estate Returns, from the Fall 2020 issue of The Journal of Alternative Investments, authors Jack Clark Francis (Baruch College) and Roger G. Ibbotson (Yale University) compare real estate investment returns to those from traditional investments like stocks and bonds. Their key focus is on real estate’s total returns—not just capital gains from rising land prices. The authors find that during the study period (1991–2018), farmland had an annualized total return of 11.4%—outperforming stocks—while residential real estate returned 9.0% and commercial real estate returned 8.5%. Most importantly, they find that rents provide the majority of investment returns from all real estate. They therefore warn investors and financial advisors not to base their investment decisions solely on how much real estate prices go up. However, they say real estate investment risk is hard to gauge because the methods used to track real estate price changes cause artificial smoothing. Real estate’s performance also shows a low correlation with that of stocks and bonds—so financial advisors and institutional investors may wish to consider adding real estate to traditional investment portfolios to help with diversification. TOPICS:Real estate, performance measurement

Private-equity commercial real estate, timberland, and farmland: market integration and information transition dynamics

Using data from the National Council of Real Estate Investment Fiduciaries (NCREIF), we examine market integration of commercial real estate and timberland–farmland assets via the Fama–MacBeth two-step approach under the intertemporal capital asset pricing framework. In addition, we study the information transition dynamics between those markets via the vector error correction model (VECM). We find evidence of market segregation and one-way information flow from the timberland–farmland market to the commercial real estate market. We conclude that commercial real estate and timberland–farmland assets are driven by different market fundamentals and that lagged timberland–farmland returns can help predict current commercial real estate returns. The only exception is during market downturns when commercial real estate and timberland–farmland markets are somewhat integrated and driven by some factors that are not specified in this study.

The Predictability of Real Estate Excess Returns: An Out-of-Sample Economic Value Analysis

We examine the predictability of private and public real estate returns using recursive, out-of-sample, linear and Markov switching models, employing a rich set of predictor variables. We find considerable improved predictive power compared to simple regression models, especially at the intermediate horizon. Next, we test whether such improved forecasting accuracy translates into a positive risk-adjusted out-of-sample performance by performing a recursive mean-variance portfolio allocation analysis. We observe significant improvements in realized Sharpe ratios and mean-variance utility scores, especially when employing Markov switching models and exploiting predictability at intermediate horizons. Furthermore, our results are robust to the inclusion of transaction costs.

Understanding the relationship between public and private commercial real estate markets

ABSTRACT This paper provides a modelling framework to examine the very low correlation at short horizons and high correlation at long horizons between private and public commercial real estate returns. For this purpose, we use a correlated, unobserved component model with a common trend and Markov-switching heteroskedasticity. This model decomposes the public and private commercial real estate prices into a common trend and interdependent cycles. The proposed model is able to endogenously capture low and high volatility regimes in real estate markets. More importantly, our model shows that the low correlation observed at short horizons between the public and private real estate markets is mainly due to the absence of any correlation in low-volatility regimes. On the other hand, the cycles, or short-run movements, in these two markets are highly correlated in high-volatility regimes.

Housing vintage and price dynamics

The vintage of a home often refers to a period-specific collection of architectural characteristics, materials, and quality. Due to age, cost of materials and construction, some vintages may not be easily reproduced — effectively rendering them supply constrained. More conventional sources of supply constraints like high levels of land use regulation influence the risk and reward profiles of homes. Are similar supply constraint-induced dynamics associated with particular vintages? In other words, does the vintage of a house influence its price dynamics? Using residential property transaction data from the Netherlands spanning 2000–2017, we construct relative price indexes for three vintages. A repeat sales model with granular location × year fixed effects and time varying maintenance controls allows for the identification of the effect of vintage on price dynamics. In general, older and more architecturally desirable vintages (pre-1900 and 1900–1945) display larger returns. From a practical point of view, the vintage driven variation in price dynamics we observe has implications for institutions concerned with modeling real estate returns and risk.

Feedback trading strategies in international real estate markets

Purpose Motivated by recent evidence that securitized real estate returns exhibit higher levels of predictability than stock market returns and that feedback trading (FT) can induce returns autocorrelation and market volatility, the purpose of this study is to examine the impact of FT strategies on long-term market volatility of eight international real estate markets (UK, Germany, France, Italy, Sweden, Australia, Japan and Hong Kong). Design/methodology/approach Assuming that the return autocorrelation may vary over time and the impact of positive feedback trading (PFT) or negative feedback trading (NFT) could be a function of return volatility, the authors use a combination of a FT model and a fractionally integrated Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) model. Findings The results are mixed, revealing that both PFT and NFT strategies persist. Specifically, the authors detect PFT in the real estate markets of France, Hong Kong and Italy as opposed to the real estate markets of Australia, Germany, Japan and Sweden where NFT was present. A noteworthy exception is the UK real estate market, with important and rational FT strategies to sustain. With respect to the long-term volatility persistence, this seems to capture the mean reversion of real estate returns in the UK and Hong Kong markets. In general, the results are not consistent with those reported in previous studies because NFT dominates PFT in the majority of real estate markets under consideration. Originality/value The main contribution of this study is the investigation of the link between short-term PFT or NFT and long-term volatility in eight international real estate markets, symmetrically. Particular attention has been given to the link between short-term FT and long-term volatility, by means of a fractionally integrated GARCH approach, a symmetric one. Moreover, investigating the relationship between returns’ volatility and investors’ strategies based on FT entails significant implications because real estate assets offer a good alternative investment for many investors and speculators.

Recognizing and realizing the value of customer-focused property management

PurposeThe purpose of this paper is to increase awareness of the value that can be derived from embracing customer service and ensuring tenant satisfaction.Design/methodology/approachThis literature review synthesizes the results of research conducted around the world to examine the value proposition of customer-focused property management. The literature was identified through a search of academic journal articles and industry publications, together with the authors' experience of working with industry practitioners. Drawing on these sources, the authors identify five emerging trends that are likely to make customer service an even more critical part of property managers' jobs and propose best practices to help property managers actualize the benefits.FindingsThree themes emerge from the literature. First, property managers can add significant value to real estate portfolios by delivering high-quality customer service to tenants. Second, emerging trends in the real estate industry are creating new opportunities for property managers to participate in the value creation process. Third, there are a number of steps property managers can take to leverage customer service to benefit the real estate investors they represent.Practical implicationsReal estate investors, and the property managers working on their behalf, can realize the advantages of customer-focused property management by adopting a series of straightforward best practices, which are discussed in the paper.Social implicationsThe trends identified and practical steps proposed are likely to be all the more relevant in the aftermath of the Covid-19 pandemic.Originality/valueThis research should increase awareness of customer-focused property management and the mechanisms through which it can affect real estate returns. The ten best practices proposed should help property managers deliver effective service to tenants and achieve the associated financial benefits for investors.