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Estate Returns (estate + return)

Distribution by Scientific Domains
Business, Economics, Finance and Accounting100%

Kinds of Estate Returns

  • real estate return
    		•

    Selected Abstracts

    Relationships between Australian real estate and stock market prices,a case of market inefficiency

    JOURNAL OF FORECASTING, Issue 3 2002
    John Okunev
    Abstract This paper explores the relationship between the Australian real estate and equity market between 1980 and 1999. The results from this study show three specific outcomes that extend the current literature on real estate finance. First, it is shown that structural shifts in stock and property markets can lead to the emergence of an unstable linear relationship between these markets. That is, full-sample results support bi-directional Granger causality between equity and real estate returns, whereas when sub-samples are chosen that account for structural shifts the results generally show that changes within stock market prices influence real estate market returns, but not vice versa. Second, the results also indicate that non-linear causality tests show a strong unidirectional relationship running from the stock market to the real estate market. Finally, from this empirical evidence a trading strategy is developed which offers superior performance when compared to adopting a passive strategy for investing in Australian securitized property. These results appear to have important implications for managing property assets in the funds management industry and also for the pricing efficiency within the Australian property market. Copyright © 2002 John Wiley & Sons, Ltd. [source]

    Illiquidity and Pricing Biases in the Real Estate Market

    REAL ESTATE ECONOMICS, Issue 3 2007
    Zhenguo Lin
    This article addresses the micro-analytic foundations of illiquidity and price dynamics in the real estate market by integrating modern portfolio theory with models describing the real estate transaction process. Based on the notion that real estate is a heterogeneous good that is traded in decentralized markets and that transactions in these markets are often characterized by costly searches, we argue that the most important aspects defining real estate illiquidity in both residential and commercial markets are the time required for sale and the uncertainty of the marketing period. These aspects provide two sources of bias in the commonly adopted methods of real estate valuation, which are based solely on the prices of sold properties and implicitly assume immediate execution. We demonstrate that estimated returns must be biased upward and risks downward. These biases can be significant, especially when the marketing period is highly uncertain relative to the holding period. We also find that real estate risk is closely related to investors' time horizons, specifically that real estate risk decreases when the holding period increases. These results are consistent with the conventional wisdom that real estate is more favorable to long-term investors than to short-term investors. They also provide a theoretical foundation for the recent econometric literature, which finds evidence of smoothing of real estate returns. Our findings help explain the apparent risk-premium puzzle in real estate,that is, that ex post returns appear too high, given their apparent low volatility,and can lead to the formal derivation of adjustments that can define real estate's proper role in the mixed-asset portfolio. [source]

    Errors in Variables, Links between Variables and Recovery of Volatility Information in Appraisal-Based Real Estate Return Indexes

    REAL ESTATE ECONOMICS, Issue 4 2006
    Peijie Wang
    The present article proposes a multivariate approach to unsmoothing appraisal-based real estate return indexes to recover the true market volatility information in real estate returns. It scrutinizes the role played by errors in variables, in conjunction with an analysis of other economic activities relevant to real estate returns, to exploit the functional relationship and the mechanism of interactions between real estate returns and these economic activities. Appraisal smoothing can therefore be detected and corrected properly and efficiently, without presuming a weakly efficient real estate market. The approach is then applied to U.K. real estate indexes as empirical examples. The results suggest a reasonable volatility in U.K. real estate investment that is close to reality. It is found that the volatility of the true market return on real estate is 1.5404,1.9282 times that of the return on the appraisal-based indexes, in contrast to figures of 2.4862,5.8720 produced by the fully unsmoothing procedure. [source]

    Market Efficiency and Return Statistics: Evidence from Real Estate and Stock Markets Using a Present-Value Approach

    REAL ESTATE ECONOMICS, Issue 2 2001
    Yuming Fu
    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. [source]

    Estimating Returns on Commercial Real Estate: A New Methodology Using Latent-Variable Models

    REAL ESTATE ECONOMICS, Issue 2 2000
    David C. Ling
    Despite their widespreao use as benchmarks of U.S. commercial real estate returns, indexes produced by the National Council of Real Estate Investment Fiduciaries (NCREIF) are subject to measurement problems that severely impair their ability to capture the true risk,return characteristics,especially volatility,of privately held commercial real estate. We utilize latent-variable statistical methods to estimate an alternative index of privately held (unsecuritized) commercial real estate returns. Latent-variable methods have been extensively applied in the behavioral sciences and, more recently, in finance and economics. Unlike factor analysis or other unconditional statistical approaches, latent variable models allow us to extract interpretable common information about unobserved private real estate returns using the information contained in various competing measures of returns that are measured with error. We find that our latent-variable real estate return series is approximately twice as volatile as the aggregate NCREIF total return index, but less than half as volatile as the NAREIT equity index. Overall, our results strongly support the use of latent-variable statistical models in the construction of return series for commercial real estate. [source]