Asymmetric Risk Measures and Real Estate Returns

Rational investors distinguish between extremely high and extremely low returns. The measures of investment risk should reflect such asymmetric risk perception. This study presents six asymmetric risk metrics and empirically tests their abilities in explaining the cross-sectional variations of real estate returns. It finds strong evidence that systematic downside risk is associated with a risk premium, and skewness provides significant explanatory power to the variation of cross-sectional property returns. On the other hand, co-skewness does not explain real estate returns well and is not a good systematic risk measure.     

Commercial Real Estate Return Performance: A Cross-Country Analysis

This paper investigates the return performance of publicly traded real estate companies. The analysis spans the 1984–1999 time period and includes return data on over 600 companies in 28 countries. The return data reveal a substantial amount of variation in mean real estate returns and standard deviations across countries. Moreover, standard Treynor ratios, which scale country excess returns by the estimated beta on the world wealth portfolio, also reveal substantial variation across countries in excess real estate returns per unit of systematic risk. However, when we estimate Jensens alphas using both single and multifactor specifications, we detect little evidence of abnormal, risk-adjusted returns at the country level. We do, however, find evidence of a strong world-wide factor in international real estate returns. Furthermore, even after controlling for the effects of world-wide systematic risk, an orthogonalized country-specific factor is highly significant. This suggests that real estate securities may provide international diversification opportunities.     

Stationarity and Cointegration in Systems with Real Estate and Financial Assets

This study examines the properties of wealth indices for investments in several asset classes (real estate, stocks, bonds, and Treasury bills), for several types of real estate (office, retail, research and development office, and warehouse), and by region (East, Midwest, South, and West). The series representing the value of investments in real estate and financial assets are not stationary; therefore, ordinary statistical procedures cannot be applied. Since many of the properties that are included in the real estate series have outside appraisals on an annual basis, especially in the fourth quarter, the real estate series may show seasonal influences. Hence, the appropriate test for cointegration is the Johansen's test, which is formulated in such a way as to allow for deterministic seasonality by the inclusion of seasonal dummy variables. The finding of cointegration implies that there is a long-run relationship between the series in the cointegrated system. When the CPI (or a proxy for inflation) is included in the three systems, the number of common factors increase to two, implying that inflation plays an important role in creating a linkage between these time series. These findings also have implications for developing portfolios comprising financial assets and real estate. The findings also have implications for developing a model to forecast real estate prices.     

Relationship Between Expected Treasury Bill and Eurodollar Interest Rates: A Fractional Cointegration Analysis

In this paper, we extend Booth and Tse's (BT)1995 analysis of fractional cointegration between theexpected Eurodollar and Treasury bill interest ratesimplied by their respective futures contracts. Thedefinition of fractional cointegration suggested byCheung and Lai (1993) and used by BT is refined sothat it requires the cointegrating relationship to bestationary as well as mean-reverting. In addition tothe Geweke and Porter-Hudak method used by BT, a moreefficient Maximum Likelihood (ML) method is used toestimate the cointegrating relationship. The LM (Engle(1982)) test indicates the possible existence of aheteroscedastic cointegrating relationship. Therefore,we use heteroscedastic models (GARCH and ExponentialGARCH) to represent the cointegrating regressioninstead of the simple homoscedastic model used by BT.The empirical evidence cannot reject the nullhypothesis of a stationary fractional cointegrationrelationship between the Eurodollar and Treasury billinterest rates.     

Assessing the Real Estate Pricing Puzzle: A Diagnostic Application of the Stochastic Discounting Factor to the Distribution of REIT Returns

This article applies a general asset-pricing framework and the volatility bounds methodology of Hansen and Jagannathan (1991) to REIT returns. The state of real estate asset pricing remains somewhat of a puzzle relative to the identification of state variables and the structural form of models. This article offers a framework whereby real estate asset-pricing models and data can be diagnosed to answer questions about the shortcomings. In addition, several nominated discount processes are investigated for success in pricing real estate securities. Although the nominated specifications demonstrate some success in satisfying the restrictions on the first and second moments of the real estate returns distribution, they do not successfully price the securities under a no-arbitrage condition. This result calls into question previous real estate performance studies that employ these risk-adjustment processes.     

Economic Risk Factors and Commercial Real Estate Returns

A great deal of research has focused on the links between stock and bond market returns and macroeconomic events such as fluctuations in interest rates, inflation rates, and industrial production. Although the comovements of real estate and other asset prices suggests that these same systematic risk factors are likely to be priced in real estate markets, no study has formally addressed this issue. This study identifies the growth rate in real per capita consumption, the real T-bill rate, the term structure of interest rates, and unexpected inflation as fundamental drivers or state variables that systematically affect real estate returns. The finding of a consistently significant risk premium on consumption has important ramifications for the vast literature that has examined the (risk-adjusted) performance of real estate, for it suggests that prior findings of significant abnormal returns (either positive or negative) that have ignored consumption are potentially biased by an omitted variables problem. The results also have important implications for dynamic asset allocation strategies that involve the predictability of real estate returns using economic data.     

Investment Policies and Excess Returns in Corporate Spin-offs: Evidence from the US Market

This article analyzes excess returns generated by corporate spin-offs with respect to changes in investment policies of the spun-off companies. Following the spin-off, the best performing spun-off companies with low growth opportunities exhibit a significant reduction in investment and the best performing high-growth spun-off companies tend to increase or maintain the previous level of investment. The results provide evidence of the existence of a direct monotonic relationship between the size of the change in the level of investment, Tobin’s Q, and excess returns based on the Fama and French (J. financ. Econ. 33: 3–56, 1993) model.     

Asymmetric Information and the Predictability of Real Estate Returns

This article examines the relation between systematic price changes and the heterogeneity of investors information sets in real estate asset markets. The empirical implications rely on a theoretical economy in which information asymmetry alters the dynamic relation between returns and trading volume. We employ a filter-rule methodology to determine predictability in returns and augment the return-based conditioning set with trading volume. The additional conditioning information is necessary since the model is underspecified when predictability is based on returns alone. Our results provide new insight into the coexistence of informational and noninformational exchange in the speculative markets for real estate assets. Specifically, we find that the predictability of real estate returns is generally more indicative of portfolio rebalancing effects than an adverse-selection problem. These results are unique in addressing the time-variation in information asymmetry.     

Further Evidence on the Integration of REIT,Bond, and Stock Returns

This study examines the integration of REIT, bond, and stock returns. Cointegration and vector autoregressive models are employed to explore the causality and long-run economic linkages among these securities. Our results show that REITs behave more like stocks and less like bonds after the structural changes in the early 1990s. Overall, results suggest that the benefits of diversification by including REITs in multiasset portfolios diminish after 1992.     

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.     

The Conditional Distribution of Real Estate Returns: Are Higher Moments Time Varying?

Previous research has shown that the returns on individual properties and listed property securities are skewed. This claim is investigated in the context of listed U.K. property companies and U.S. REITs. In particular, the shape of the conditional distribution of total monthly returns is examined for a group of 20 U.K. companies and 20 REITs. Also investigated is the claim that the skewness found in property returns varies over time. Using the model of Hansen (1994), it is found that while a large portion of property security returns in the sample do exhibit skewness in the conditional distribution only in a few instances is there time variation in the skewness parameter. There is little evidence to suggest that skewness is associated with the economic cycle.     

Cointegration Analysis of Audit Pricing Model: A Panel Unit Root Test Approach

In this study, we provide evidence on the stationarity of real audit fees and the major explanatory variables frequently used in the audit pricing models from a pooled data set, using panel unit root tests developed by Im et al. (1997). The panel unit root test supports the hypothesis of non‐stationarity of audit fees and their major determinants. We demonstrate that variables in the audit pricing model that were previously found to have impact on audit fees may turn out to be useless when more powerful tests like panel tests are applied to these variables. Our evidence implies that failing to employ appropriate procedure to test cointegration and to specify the appropriate model for audit fees and their determinants would generate results that may have exaggerated the effects of some variables on audit fees.     

Asymmetric Cointegration,Nonlinear ARDL,and the J-Curve: A Bilateral Analysis of China and Its 21 Trading Partners

This article follows the nonlinear Autoregressive Distributed Lag (ARDL) error-correction methodology to explore nonlinearity in the relationship between the trade balances and the real exchange rates for China and its 21 partners. We find evidence for short-run asymmetric effects of exchange rate in cases of 18 partners, short-run adjustment asymmetry in cases of 11 partners, short-run cumulative asymmetry in cases of seven partners, and a significant long-run asymmetric effect cases of five partners. We find support for the “J-curve” that is only due to appreciation or depreciation of the Yuan in cases of five partners, including the U.S.     

Structural Breaks and Predictive Regression Models of Aggregate U.S. Stock Returns

In this article we examine the structural stability of predictiveregression models of U.S. quarterly aggregate real stock returnsover the postwar era. We consider predictive regressions modelsof S&P 500 and CRSP equal-weighted real stock returns basedon eight financial variables that display predictive abilityin the extant literature. We test for structural stability usingthe popular Andrews SupF statistic and the Bai subsample procedurein conjunction with the Hansen heteroskedastic fixed-regressorbootstrap. We also test for structural stability using the recentlydeveloped methodologies of Elliott and Müller, and Baiand Perron. We find strong evidence of structural breaks infive of eight bivariate predictive regression models of S&P500 returns and some evidence of structural breaks in the threeother models. There is less evidence of structural instabilityin bivariate predictive regression models of CRSP equal-weightedreturns, with four of eight models displaying some evidenceof structural breaks. We also obtain evidence of structuralinstability in a multivariate predictive regression model ofS&P 500 returns. When we estimate the predictive regressionmodels over the different regimes defined by structural breaks,we find that the predictive ability of financial variables canvary markedly over time.     

Optimal Estimation of the Risk Premium for the Long Run and Asset Allocation: A Case of Compounded Estimation Risk

It is well known that an unbiased forecast of the terminal valueof a portfolio requires compounding at the arithmetic mean returnover the investment horizon. However, the maximum-likelihoodpractice, common with academics, of compounding at the estimatorof mean return results in upward biased and highly inefficientestimates of long-term expected returns. We derive analyticallyboth an unbiased and a small-sample efficient estimator of long-termexpected returns for a given sample size and horizon. Both estimatorsentail penalties that reduce the annual compounding rate asthe investment horizon increases. The unbiased estimator, whichis far lower than the compounded arithmetic average, is stillvery inefficient, often more so than a simple geometric estimatorknown to practitioners. Our small-sample efficient estimatoris even lower. These results compound the sobering evidencein recent work that the equity risk premium is lower than suggestedby post-1926 data. Our methodology and results are robust toextensions such as predictable returns. We also confirm analyticallythat parameter uncertainty, properly incorporated, producesoptimal asset allocations, in stark contrast to conventionalwisdom. Longer investment horizons require lower, not higher,allocations to risky assets.     

A Spatial Model of Housing Returns and Neighborhood Substitutability

This article provides a method for estimating housing indices at the local level. It develops a distance-weighted repeat-sales procedure to exploit the factor structure of the error-covariance matrix in the repeat-sales model. A distance function defined in characteristic and geographical space provides weights for the generalized least-squares model, and allows the use of all of the repeated sales in a metropolitan area to measure returns for the specific neighborhood of interest. We use distance-weighted repeat sales to estimate return indices for all zip codes in the San Francisco Bay area over the period 1980--1994.When distance is defined in terms of socioeconomic characteristics, we find that median household income is the salient variable explaining covariance of neighborhood housing returns. Racial composition and educational attainment, while significant, are much less influential. Zip-code level indices often deviate dramatically from the citywide index, depending upon income levels. This has implications for investors and lenders. Our results indicate that rates of return may vary considerably within a metropolitan area. Thus, simply using broad metropolitan area indices as a proxy for capital appreciation within a specific neighborhood may not be justified.     

Real estate returns,money and fiscal deficits: Is the real estate market efficient?

This research examines the causal relationship between several financial variables and a portfolio of real estate returns using monthly data from January 1965 to December 1986. The empirical analysis is based on multivariate Granger-causality tests in conjunction with Akaike's final prediction error criterion. The results indicate that measures approximating monetary policy and market returns play an important role in causing changes in real estate returns. In particular, our findings suggest that base money and market returns have had significant lagged effects on current real estate returns.     

The Information Signaling Hypothesis of Dividends: Evidence from Cointegration and Causality Tests

This paper uses cointegration and causality tests to study the temporal behavior of dividends and earnings at the individual firm level. We find that, for a sample of 143 non‐utility firms, approximately one‐fifth of the firms exhibits a temporal relationship between dividends and earnings that is consistent with the information signaling hypothesis of dividends. In the case of 72 utilities, about a third exhibit dividend policies that are consistent with the signaling notion of dividends. Further examination of firm characteristic differences between signaling and non‐signaling firms shows that, in the case of non‐utility firms, signaling firms tend to be smaller, have a lower growth rate of total assets, and have a higher leverage ratio. In the case of utilities, we find no major differences in firm characteristics between signaling and non‐signaling firms.     

Empirical Analysis of Stock Returns and Volatility: Evidence from Seven Asian Stock Markets Based on TAR-GARCH Model

This paper investigates the time-series behavior of stock returns for seven Asian stock markets. In most cases, higher average returns appear to be associated with a higher level of volatility. Testing the relationship between stock returns and unexpected volatility, the evidence shows that four out of seven Asian stock markets have significant results. Further analyzing the relationship between stock returns and time-varying volatility by using Threshold Autoregressive GARCH(1,1)-in-mean specification indicates that the null hypothesis of no asymmetric effect on the conditional volatility is rejected for the daily data. However, the null cannot be rejected for the monthly data.     

Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations

Maximum-likelihood estimates of the parameters of stochasticdifferential equations are consistent and asymptotically efficient,but unfortunately difficult to obtain if a closed-form expressionfor the transitional probability density function of the processis not available. As a result, a large number of competing estimationprocedures have been proposed. This article provides a criticalevaluation of the various estimation techniques. Special attentionis given to the ease of implementation and comparative performanceof the procedures when estimating the parameters of the Cox–Ingersoll–Rossand Ornstein–Uhlenbeck equations respectively.