11,960 research outputs found
The Magnitude of Random Appraisal Error in Commercial Real Estate Valuation
Analysis of more than seven hundred pairs of simultaneous independent appraisals of institutional-grade commercial properties shows that the standard deviation of the random component of appraisal error is approximately 2%. Random appraisal error appears constant across both time and the institutional-grade investment universe, except during infrequent periods of real estate market gridlock. Most appraisal error is deterministic in nature, even though it usually appears random in routine cross-sectional analysis. Such appraisal error can be constrained and reduced by investment management control systems.
Serial Persistence in Equity REIT Returns
Annual and monthly REIT returns display statistically significant serial persistence, although the two types of persistence behavior are qualitatively different. By contrast, quarterly REIT returns do not display serial persistence. This strongly suggests that linear multifactor market models cannot describe REIT investment behavior. Annual REIT returns fail to reflect corresponding persistence behavior in underlying real estate returns precisely when the REITs are large enough to attract institutional investor interest. Institutional investors move in and out of large-capitalization REITs in ways that negatively impact investment returns.
Systematic Behavior in Real Estate Investment Risk: Performance Persistence in NCREIF Returns
Serial dependence of total annual returns in the NCREIF database is shown to be statistically significant in the first and fourth quartiles of disaggregated data between 1978 and 1994. More precisely, superior performance is generally followed by continued superior performance, and inferior performance is generally followed by continued inferior performance. In contrast, there is virtually no evidence to support serial dependence in the second or third quartiles, whether combined or taken separately. The empirical rejection of serial independence among real estate returns calls into question the conclusions of research based upon models that incorporate the assumption of serial independence.
How Middle and High School Educators and Students Adapt to the Challenges of Advancing Technology
A thorough review of the literature was used to examine whether our middle and high school educational system is adapting to the technological changes in a constructive or destructive way. The research not only identified critical issues indicated within the literature review but also issues that remain controversial and those that have not received much consideration. The cultural diversity of not only our schools but the whole society as well offers a great magnitude of challenges. This review emulates the diverse responses by those men and women whom have experienced and worked with the educational systems. The benefits and burdens technology brings to the table for all school districts reflects the responsibility students and educators have when deciding which technology to implement into the learning experiences. Technology is and should be integrated into educational programs so that it benefits the majority of all students
The Shape of Australian Real Estate Return Distributions and Comparisons to the United States
Investment risk models with variance provide a better description of distribution of individual property returns in the Property Council of Australia data base from 1985 to 1996 than normally distributed risk models. The shape of the distribution of Australian property returns is virtually indistinguishable from the shape of United States property returns in the NCREIF Property Index for the years 1980 to 1992. Australian real estate investment risk is heteroscedastic, like its US counterpart, but the characteristic exponent of the investment risk function is constant across time and property type. It follows that portfolio management and asset diversification techniques that rely upon finite-variance statistics are as ineffectual for the Australian real estate market as they have been found to be for the United States.
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