Testing the predictability and efficiency of securitized real estate markets

This paper conducts tests of the random walk hypothesis and market efficiency for 14 national public real estate markets. Random walk properties of equity prices influence the return dynamics and determine the trading strategies of investors. To examine the stochastic properties of local real estate index returns and to test the hypothesis that public real estate stock prices follow a random walk, the single variance ratio tests of Lo and MacKinlay (1988) as well as the multiple variance ratio test of Chow and Denning (1993) are employed. Weak-form market efficiency is tested directly using non-parametric runs tests. Empirical evidence shows that weekly stock prices in major securitized real estate markets do not follow a random walk. The empirical findings of return predictability suggest that investors might be able to develop trading strategies allowing them to earn excess returns compared to a buy-and-hold strategy

Further evidence on the (in-) efficiency of the U.S. housing market

Extending the controversial findings from relevant literature on testing the efficient market hypothesis for the U.S. housing market, the results from the monthly and quarterly transaction-based Case-Shiller indices from 1987 to 2009 provide further empirical evidence on the rejection of the weak-form version of efficiency in the U.S. housing market. In addition to conducting parametric and non-parametric tests, we apply technical trading strategies to test whether or not the inefficiencies can be exploited by investors earning excess returns. The empirical findings suggest that investors might be able to obtain excess returns from both autocorrelation- and moving average-based trading strategies compared to a buy-and-hold strategy

Financial and corporate social performance in the UK listed firms: the relevance of non-linearity and lag effects

Using environmental, social and governance scores compiled by Reuters Datastream for each company’s corporate social performance (CSP), we examine the relationship between CSP and corporate financial performance (CFP) of 314 UK listed companies over the period 2002–2015. We further evaluate the relationship between prior and subsequent CFP and prior and subsequent CSP. Based on the system-GMM estimation method, we provide direct evidence that suggests that while CFP and CSP can be linked linearly; however, when we examine the impact of CSP on CFP, the association is more non-linear (cubic) than linear. Our results suggest that firms periodically adjust their level of commitment to society, in order to meet their target CSP. The primary contributions of this paper are testing (1) the non-monotonous relationship between CSP and CFP, (2) the lagged relationship between the two and the optimality of CSP levels, and (3) the presence of a virtuous circle. Our results further suggest that CSP contributes to CFP better during post-crisis years. Our findings are robust to year-on-year changes in CFP and CSP, financial versus non-financial firms, and the intensity of corporate social responsibility (CSR) engagement across industries

Changes in REIT Liquidity 1990-1994: Evidence from Intra-day Transactions

This study uses data on intra-day transactions to analyze whether real estate investment (REIT) liquidity as measured by the bid-ask spread changed from 1990 to 1994, a period during which the industry's market capitalization increased from $8.7 billion to$45 billion. REIT percentage spreads (spread as percentage of share price) narrowed significantly, primarily attributable to higher share prices rather than narrower dollar-value spreads. An empirical model is used to analyze the determinants of percentage spreads. Return variance and share price, not market capitalization are found to be the primary determinants of percentage spreads in both periods. This suggests that the liquidity of REIT securities is similar to that of non-REIT securities with similar prices and return variance. In addition, percentage spreads are wider for REITs trading on the NASDAQ. Copyright American Real Estate and Urban Economics Association.

Valuation in US Commercial Real Estate

"We consider a log-linearized version of a discounted rents model to price commercial real estate as an alternative to traditional hedonic models. First, we verify a key implication of the model, namely, that cap rates forecast commercial real estate returns. We do this using two different methodologies: time series regressions of 21 US metropolitan areas and mixed data sampling (MIDAS) regressions with aggregate REIT returns. Both approaches confirm that the cap rate is related to fluctuations in future returns. We also investigate the provenance of the predictability. Based on the model, we decompose fluctuations in the cap rate into three parts: (i) local state variables (demographic and local economic variables); (ii) growth in rents; and (iii) an orthogonal part. About 30% of the fluctuation in the cap rate is explained by the local state variables and the growth in rents. We use the cap rate decomposition into our predictive regression and find a positive relation between fluctuations in economic conditions and future returns. However, a larger and significant part of the cap rate predictability is due to the orthogonal part, which is unrelated to fundamentals. This implies that economic conditions, which are also used in hedonic pricing of real estate, cannot fully account for future movements in returns. We conclude that commercial real estate prices are better modelled as financial assets and that the discounted rent model might be more suitable than traditional hedonic models, at least at an aggregate level." Copyright 2007 The Authors Journal compilation (c) 2007 Blackwell Publishing Ltd.