Why Do REIT Prices Change? The Information Content of Barron's “The Ground Floor”

This article examines the information content in a series of market commentaries covering the publicly traded real estate market. The data are constructed from REIT-specific announcements published in a widely disseminated source of market commentary. The empirical methodology is designed to test whether the unexpected price change and unexpected volume are significant on the announcement day. The results demonstrate that the market commentaries provide information that impacts prices and that investors use this information in their trading. Additional analysis suggests that prices change more in the period following the REIT boom than during an earlier period. This result seems somewhat puzzling given recent studies that report an increase in REIT market liquidity.     

Returns transmission, value at risk, and diversification benefits in international REITs: evidence from the financial crisis

We examine daily cross-market return interactions and downside risk between a US REIT returns index and the return indexes of twelve international REIT markets. These relationships are investigated for a period of normal REIT market conditions as well as for periods of inflating and collapsing REIT prices. We find that US REIT returns are contemporaneously correlated with other REITs most strongly during the bubble and crash market conditions where the US REIT market is an almost unilateral transmitter of returns. We also find that the Value at Risk (VaR) of the least capitalized REIT markets is proportionally higher during base/normal market conditions but that the largest REIT markets have the highest VaR contribution during the crash (financial crisis) period. Overall, our evidence indicates that REIT market risk shifted to the largest REIT markets and that diversification benefits eroded considerably during turbulent market conditions.     

An Examination of Macroeconomic Effects on the Liquidity of REITs

In this research, we investigate the effects of changes in and levels of selected macroeconomic variables on the liquidity of Real Estate Investment Trust (REIT, henceforth) stocks. We study in particular REIT market trading liquidity and REIT funding liquidity. We use debt service coverage ratios, loan-to-value ratios and the number of loans on commercial commitments as proxies for the funding liquidity of REITs. We use Amihud Illiquidity measurement and Turnover Ratio measurement to estimate REIT market trading liquidity. Our results are fourfold: one, funding liquidity is influenced by changes in macroeconomic factors; two, macroeconomic effects are different across phases of the business cycle; three, funding liquidity is significantly positively related to REIT market liquidity (this is supportive of Brunnermeier and Petersen’s Review of Financial Studies, 22:2201–2238 (2009) findings); and four, these effects vary across economic regimes. A key outcome of this work is that increases in debt to equity reduce market liquidity for REIT stocks.     

Information, Trading, and Volatility: Evidence from Weather-Sensitive Markets

We find that trading‐ versus nontrading‐period variance ratios in weather‐sensitive markets are lower than those in the equity market and higher than those in the currency market. The variance ratios are also substantially lower during periods of the year when prices are most sensitive to the weather. Moreover, the comovement of returns and volatilities for related commodities is stronger during the weather‐sensitive season, largely due to stronger comovement during nontrading periods. These results are consistent with a strong link between prices and public information flow and cannot be explained by pricing errors or changes in trading activity.     

Trading activity,dealer concentration and foreign exchange market quality

We study the relation between foreign exchange market quality and both trading activity and dealer concentration by considering two currency pairs with significant differences along both dimensions – the Euro–US dollar and Canadian dollar–US dollar. A variance ratio test reveals over-reaction in currency prices, but that this is smallest when trading activity is high and dealer concentration at its peak. A GARCH model shows that over-reaction declines as trading activity and dealer concentration increase, with the results being stronger for the Euro. Our results confirm that trading activity is an important determinant of market quality, but also point to a significant role for dealer concentration.     

Depreciation-Related Capital Gains,Differential Tax Rates,and the Market Value of Real Estate Investment Trusts

We develop a model for valuing U.S. real estate investment trusts (REITs) that considers the tax liability impounded in REITs’ property portfolios. This liability is a function of the portfolio’s accumulated depreciation and is driven by different tax rates applied to individual components of the total gain from property sales. These two components are the capital gain resulting from the sale of property at a price higher than its cost and the gain due to the recapture of depreciation taken during the use of the property. Our measure of value is the REIT’s net asset liquidation value (NALV). The metric of REIT value currently used by analysts is a REIT’s net asset value (NAV), but a REIT’s NAV will always be greater than the NALV and therefore overestimate market value, all else equal. Finally, using observed market prices for REITs, we provide evidence that NALVs give superior estimates of REIT market prices than do NAVs.     

Reits’ Price Reaction to Unexpected FFO Announcements

This study examines the reaction of REIT prices to unexpected FFO announcements. Using both the traditionally constrained models and an unconstrained model, we find that the market reacts significantly when REITs announce unexpected FFO with a stronger response for positive than negative surprises. Also, we find that FFO explains significantly more variance in abnormal returns than net income supporting our conjecture that FFO, being more accurately reflective of cash flow, provides more useful information to investors than traditional GAAP measures. Our results are robust to different specifications. The results also suggest that the traditional approaches have been misspecified.     

Have Equity REITs Experienced Periodically Collapsing Bubbles?

This paper uses the momentum threshold autoregressive (MTAR) model and the residuals-augmented Dickey–Fuller (RADF) test to examine the possibility of Evans’ (1991) periodically collapsing bubbles in the equity REIT market. The results are mixed. The MTAR model indicates that overall real equity REIT prices and dividends are cointegrated with asymmetric adjustment towards the long-run equilibrium. However, the estimated coefficients of the MTAR model do not indicate the presence of periodically collapsing bubbles. Adjustment in the standard cointegration tests of bubbles for skewness and excess kurtosis via the RADF test fails to reject the null hypothesis of no cointegration, leaving the possibility of periodically collapsing bubbles. The MTAR and RADF results with respect to equity REIT sub-sectors are mixed. Lodging is the only sub-sector in which both the MTAR and RADF results support periodically collapsing bubbles. Moreover, market fundamentals proxied by two alternative measures of capacity utilization do not explain either real equity REIT prices or dividends.     

An Empirical Investigation of Herding Behavior in the U.S. REIT Market

Our study investigates the market-wide herding behavior in the U.S. equity REIT market. Utilizing the quantile regression method, we find that herding is more likely to be present in the high quantiles of the REIT return dispersion. This implies that REIT investors tend to herd under turbulent market conditions. Our results also support the asymmetry of herding behaviors, that is, herding is more likely to occur and becomes stronger in declining markets than in rising markets. In addition, our findings show that the current financial crisis has caused a change in the circumstances under which herding can occur, as we find that during the current crisis REIT investors may not start to herd until the market becomes extremely turbulent whereas during the relatively normal period before the crisis, investors tend to herd when the market is moderately turbulent. Finally, we find that compared with the case of the ‘pre-modern’ era, REIT investors are more likely to herd in the ‘modern’ era, during which herding usually occurs when the market becomes tumultuous. This implies that the switch of REITs from passive externally managed entities into active self-managed ones has made the investors more responsive to market sentiment.     

Are There Rational Speculative Bubbles in REITs?

This study tests for the presence of rational speculative bubbles in the Equity REIT industry. We analyze REIT prices using a vector of macroeconomic fundamentals. Using the unit root test and cointegration procedures, we find no evidence of rational bubbles in the REIT market. Tests for duration dependence in the returns series show no evidence of negative duration dependence, suggesting that REIT markets are not affected by rational bubbles. Applying the same tests, we find no evidence of rational speculative bubbles in the Russell 2000 index, a proxy for small-cap stocks.     

限制交易政策如何影响期现关系?——对股指期货价格发现功能的实证检验

本文利用2015年中国股市大幅下跌期间,对股指期货严格限制交易政策这一独特事件前后的高频数据,研究限制交易政策对股指期货与股票市场价格引导关系的影响。利用I-S模型和分位数回归方法的实证结果表明:限制交易政策实施前,股指期货对股票市场的价格影响更强,尤其表现在价格急剧下跌时期;限制交易政策显著增加了期货市场交易成本,从而降低了期货市场的信息份额,削弱了其对股票市场的价格影响,并且改变了期货价格对现货价格“助跌强于助涨”的影响模式,增强了股指期货在价格上涨时对股票市场的影响。研究结果一方面直接量化了期货交易成本变动对其价格发现功能的负面影响,另一方面也从价格引导关系的视角提供了股市危机时期股指期货限制交易政策监管效果的实证证据。     

Effects of monetary policy on the REIT returns: Evidence from the United Kingdom

In this paper, we analyze whether a monetary policy based on three main variables (inflation, money supply, and output gap) has a nonlinear impact on real estate investment trust (REIT) markets. In addition, we extend our analysis to examine whether these monetary policy components impact the possibility of boom and bust regimes occurring in the market. Empirically, we propose different Markov-switching model variants to determine the nonlinear time-varying impact of monetary policy on the REIT market. Our results show the monetary policy environment is supposed to affect, on one hand, the REIT returns and, on the other hand, the possibility of boom and bust markets. We prove that expansionary monetary policy has an impact only in the case of boom market. However, an increase in the inflation rate decreases the probability of remaining in the bust regime. As a consequence, we have already outlined several monetary transmission mechanisms that show house prices to have important effects on aggregate demand. Our results confirm that REIT markets are not efficient.     

Equity Capital Flows and Demand for REITs

REITs are attractive to investors due to their unique characteristics such as high dividend yields, low correlation with common stocks, and a potential hedge against inflation. Thus the market demand curve of REIT equities may not be horizontal. This paper examines the shape of the market demand curve for REIT equities by employing REIT equity capital flows as a proxy for REIT aggregate demand. Our results do not support a downward demand curve for REIT equities. That is, we do not find evidence for the price-pressure effect in REIT returns. Instead, we find it is REIT returns that affect REIT equity capital flows rather than REIT equity flows that affect REIT returns. The results are consistent when we allow for the presence of market fundamental variables in our analysis. In addition, a variance decomposition analysis suggests that REIT equity capital flows do not cause revisions in expected cash flows (dividends) that are strong enough to impact REIT returns. Thus our findings are consistent with implications that the market demand curve for REIT equities is horizontal.     

Noise trading and the price formation process

This study proposes the dispersion in daily net initiated order flow across brokers as a proxy for the level of noise trading in a stock, and applies this proxy to test some basic implications of market microstructure theory. We use data from the Australian Stock Exchange, a computerized limit order market where price, quantity, and broker identity for each incoming order are shown on broker screens. We find daily movements in our noise measure are positively associated with trading volume and market depth, and negatively related to the bid-ask spread. We find monthly movements in our noise measure are negatively associated with the probability of informed trading, and positively correlated with the arrival rate of uninformed traders. We also find the sensitivity of stock prices to net initiated order flow decreases in the level of noise trading. In addition we find that, after controlling for noise trading, the sensitivity of stock prices to net initiated order flow is significantly greater on Mondays. These empirical results consistently support the implications of various models of market microstructure, suggesting that our proxy provides useful information as a daily measure of noise trading.     

Disagreement and asset prices

How do differences of opinion affect asset prices? Do investors earn a risk premium when disagreement arises in the market? Despite their fundamental importance, these questions are among the most controversial issues in finance. In this paper, we use a novel data set that allows us to directly measure the level of disagreement among Wall Street mortgage dealers about prepayment speeds. We examine how disagreement evolves over time and study its effects on expected returns, return volatility, and trading volume in the mortgage-backed security market. We find that increased disagreement is associated with higher expected returns, higher return volatility, and larger trading volume. These results imply that there is a positive risk premium for disagreement in asset prices. We also show that volatility in and of itself does not lead to higher trading volume. Instead, only when disagreement arises in the market is higher uncertainty associated with more trading. Finally, we are able to distinguish empirically between two competing hypotheses regarding how information in markets gets incorporated into asset prices. We find that sophisticated investors appear to update their beliefs through a rational expectations mechanism when disagreement arises.     

What Determines Stock Price Synchronicity in REITs?

This paper studies the behavior of REIT stock price synchronicity for the years 1997 through 2006. Theory suggests that REIT stock prices should be largely independent of market changes; and, at the very least, REITs should have a low covariance with other assets, including other REIT stocks. The evidence presented below does not support this view. Instead, synchronicity appears to be quite high in the equity REIT market, especially among REITs that larger and more liquid. We also find that REIT stock price synchronicity is negatively related to hedge fund ownership, but positively related to pension fund and insurance company ownership. The evidence further suggests that synchronicity is the highest among industrial and regional mall REITs, and lower among apartment, health care, and mixed property REITs.     

The price discovery of day trading activities in futures market

Access to information is necessary for market transparency. However, contrary to trading volume and open interest, information related to day trading activities is rarely available. By incorporating unexplored day trading volume in the literature, this paper demonstrates that both the expected open interest and expected day trading volume are consistently and positively correlated with returns, but that one-lagged day trading volume is negatively correlated with futures returns. Meanwhile, both expected and unexpected day trading volume are negatively correlated with volatility, suggesting that arbitrage activities related to unexpected day trading volume may accelerate the movement of futures prices to a new equilibrium. Moreover, open interest provides liquidity but increases volatility. Finally, we strongly suggest that day trading transaction information be released by futures exchanges to achieve greater transparency.     

On the prediction of financial distress in developed and emerging markets: Does the choice of accounting and market information matter? A comparison of UK and Indian Firms

We examine differences in price delay for a sample of real estate investment trust (REIT) and non-REIT matched pairs. Results suggest an economically and statistically higher level of price delay for REIT securities, which implies heightened frictions that increase the time needed for new information to be impounded into the prices of REIT shares. The primary drivers for the observed delay differential include differences in idiosyncratic volatility, market risk, and the number of days traded. Within-REIT determinants of delay confirm findings for the pooled sample of matched pairs. Importantly, we infer find that REIT investors are not compensated for restricted information flow, as excess returns are unrelated to the price delay.     

Information Uncertainty and the Post-Earnings-Announcement Drift Anomaly: Insights from REITs

This is the first study to examine the post-earnings-announcement drift anomaly in a Real Estate Investment Trust (REIT) context. The efficient markets hypothesis suggests that unexpected earnings should be fully incorporated into asset prices soon after being publicly announced. We hypothesize that publicly announced earnings signals may be more certain for REITs due to the presence of a parallel (private) asset market, suggesting less drift for REIT stocks. However, we find a large REIT drift component that is both statistically and economically significant. Furthermore, while the initial earnings surprise response is more muted for REITs, we find that the magnitude of the drift is significantly larger for REITs than for ordinary common stocks (NonREITs). Thus, information does not appear to move between the private and public asset markets in such a way as to render REIT earnings signals more certain than NonREIT earnings signals.     

Investor Sentiment and REIT Returns

Recent advances in the field of behavioral finance have given a fillip to the use of behavioral factors in asset pricing models. This study adds to the understanding of the REIT return generating process by exploring the behavioral impact of investor sentiment on REIT returns. The results show that when investors are optimistic (pessimistic), REIT returns become higher (lower). These findings are robust when conventional control variables are considered. Empirical analysis indicates steady erosion in the importance of the default and term structure interest rate variables previously considered as important determinants of REIT returns. Previous noise trading papers that consider the impact of institutional traders conclude that institutional investors cannot arbitrage away noise trader risk. The results of this paper find an exception in the case of small REITs. Examination of REITs based on size reveals that the return generating process of small REITs differs from that of mid-size and large REITs. Analysis of the return generating process by performance shows high performance REITs are more sensitive to the independent variables in the model as compared to the low and mid performance REITs.