BOCA RATON, Fla., May 27, 2015 /PRNewswire-USNewswire/ -- The
method used to calculate Standard & Poor's Case-Shiller Home
Price Indices, the most trusted benchmark for U.S. residential real
estate prices, contains a flaw that likely could lead to misstating
its monthly estimates, according to a newly published study led by
faculty at Florida Atlantic
University.
The paper published in the Journal of Real Estate Research
identifies an important deficiency in the Weighted Repeated Sales
(WRS) method developed by economists Karl
Case and Robert Shiller,
which compares repeat sales of the same homes in an effort to study
home pricing trends both nationally and in 20 metropolitan areas
across the country.
The critical flaw in Case-Shiller's method, the paper's authors
contend, is its omission of the market risk factor. Ping Cheng, Ph.D., professor of finance in FAU's
College of Business, explained what initially got him and his
colleagues thinking about the index methodology was an assertion by
Case and Shiller in their original work, in which they stated that
over longer time intervals, the price changes for an individual
home are more likely to be caused by factors other than market
forces.
"It just seemed strange that a study aimed at monitoring market
price changes will assert that market forces has no bearing on such
changes," said Cheng.
Cheng and his colleagues then conducted a closer examination on
the Case-Shiller methodology and concluded that the omission of the
market risk factor by Case and Shiller is "mathematically and
conceptually unjustified." They propose an alternative weight model
that properly incorporates the market risk factor.
Traditionally, it's widely accepted that security asset price in
an efficient market follows the so-called random walk, a theory
that states that the past movement or direction of a stock or
overall market cannot be used to predict its future movement. In
their 1989 paper, Case and Shiller conclude that the real estate
market is not efficient because property prices clearly do not
follow the random walk.
"If the housing market is inefficient, price changes over the
time intervals between the paired sales cannot be described as
random walk," Cheng said. "So how do you measure and quantify the
impact of the holding period (time interval) on return, the risk,
property price and volatility?"
"Case and Shiller did not try to answer this question," he
added. "Instead they simply asserted that market risk has no
bearing on the weight estimation, and ignored it."
The study's authors tackle this question and present extensive
empirical evidence on the relationship between real estate market
risk and the holding time (or the time interval between paired
sales). The findings are presented in what they call risk lines --
direct observations from a wide range of the real estate market and
submarket indices without resorting to complex statistical
manipulations.
To see whether the methodological modification makes a
difference in the resulting indices, Cheng and his fellow
researchers use a large sample of repeat sales from the
Washington D.C. area and construct
three repeat sales indices using the original regression
methodology developed in 1963 by Bailey, Muth and Nourse (BMN), the
Case-Shiller's Weighted Repeated Sales (WRS) method and their
modified WRS method. Their comparison shows that market risk
clearly affects index performance. In times of high market
volatility such as the recent housing boom and bust period, the
Case-Shiller index was found to perform worse than the original BMN
method.
"Our results suggest that, while weighting the paired sales is
important, not weighting properly can be worse than not weighting
at all," Cheng said. "Given that the indices are the basis for huge
amount of tradable housing derivatives (futures and options), there
could be real money at stake in the indices' accuracy."
Cheng co-authored the paper with Zhenguo
Lin, Ph.D., professor of finance at California State University, Fullerton;
Xin He, Ph.D., professor at Dongbei
University of Finance and Economics in China; and Yingchun
Liu, assistant professor in the Department of Finance,
Insurance and Real Estate at Laval
University in Canada.
About Florida Atlantic
University:
Florida Atlantic University,
established in 1961, officially opened its doors in 1964 as the
fifth public university in Florida. Today, the University, with an annual
economic impact of $6.3 billion,
serves more than 30,000 undergraduate and graduate students at
sites throughout its six-county service region in southeast
Florida. FAU's world-class
teaching and research faculty serves students through 10 colleges:
the Dorothy F. Schmidt College of Arts and Letters, the College of
Business, the College for Design and Social Inquiry, the College of
Education, the College of Engineering and Computer Science, the
Graduate College, the Harriet L. Wilkes Honors College, the Charles
E. Schmidt College of Medicine, the Christine E. Lynn College of
Nursing and the Charles E. Schmidt College of Science. FAU is
ranked as a High Research Activity institution by the Carnegie
Foundation for the Advancement of Teaching. The University is
placing special focus on the rapid development of critical areas
that form the basis of its strategic plan: Healthy aging, biotech,
coastal and marine issues, neuroscience, regenerative medicine,
informatics, lifespan and the environment. These areas provide
opportunities for faculty and students to build upon FAU's existing
strengths in research and scholarship. For more information, visit
www.fau.edu.
Contact: Jim Hellegaard,
561-319-2233, jhellegaard@fau.edu
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SOURCE Florida Atlantic
University